Upload folder using huggingface_hub

checkpoint-13500/1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 384,
+  "pooling_mode_cls_token": false,
+  "pooling_mode_mean_tokens": true,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true
+}

checkpoint-13500/README.md

@@ -0,0 +1,525 @@
+---
+base_model: sentence-transformers/all-MiniLM-L6-v2
+datasets:
+- youssefkhalil320/pairs_three_scores_v5
+language:
+- en
+library_name: sentence-transformers
+license: apache-2.0
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:80000003
+- loss:CoSENTLoss
+widget:
+- source_sentence: durable pvc swim ring
+  sentences:
+  - flaky croissant
+  - urban shoes
+  - warm drinks mug
+- source_sentence: iso mak retard capsules
+  sentences:
+  - savory baguette
+  - shea butter body cream
+  - softwheeled cruiser
+- source_sentence: love sandra potty
+  sentences:
+  - utensil holder
+  - olive pants
+  - headwear
+- source_sentence: dusky hair brush
+  sentences:
+  - back compartment laptop
+  - rubber feet platter
+  - honed blade knife
+- source_sentence: nkd skn
+  sentences:
+  - fruit fragrances nail polish remover
+  - panini salmon
+  - hand drawing bag
+---
+
+# all-MiniLM-L6-v8-pair_score
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) on the [pairs_three_scores_v5](https://huggingface.co/datasets/youssefkhalil320/pairs_three_scores_v5) dataset. It maps sentences & paragraphs to a 384-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Sentence Transformer
+- **Base model:** [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) <!-- at revision c9745ed1d9f207416be6d2e6f8de32d1f16199bf -->
+- **Maximum Sequence Length:** 256 tokens
+- **Output Dimensionality:** 384 tokens
+- **Similarity Function:** Cosine Similarity
+- **Training Dataset:**
+    - [pairs_three_scores_v5](https://huggingface.co/datasets/youssefkhalil320/pairs_three_scores_v5)
+- **Language:** en
+- **License:** apache-2.0
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
+- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+
+### Full Model Architecture
+
+```
+SentenceTransformer(
+  (0): Transformer({'max_seq_length': 256, 'do_lower_case': False}) with Transformer model: BertModel 
+  (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
+  (2): Normalize()
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("sentence_transformers_model_id")
+# Run inference
+sentences = [
+    'nkd skn',
+    'hand drawing bag',
+    'panini salmon',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 384]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities.shape)
+# [3, 3]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### pairs_three_scores_v5
+
+* Dataset: [pairs_three_scores_v5](https://huggingface.co/datasets/youssefkhalil320/pairs_three_scores_v5) at [3d8c457](https://huggingface.co/datasets/youssefkhalil320/pairs_three_scores_v5/tree/3d8c45703846bd2adfaaf422abafbc389b283de1)
+* Size: 80,000,003 training samples
+* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>score</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | sentence1                                                                        | sentence2                                                                        | score                                                          |
+  |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------|
+  | type    | string                                                                           | string                                                                           | float                                                          |
+  | details | <ul><li>min: 3 tokens</li><li>mean: 6.06 tokens</li><li>max: 12 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 5.71 tokens</li><li>max: 13 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.11</li><li>max: 1.0</li></ul> |
+* Samples:
+  | sentence1                            | sentence2                              | score            |
+  |:-------------------------------------|:---------------------------------------|:-----------------|
+  | <code>vanilla hair cream</code>      | <code>free of paraben hair mask</code> | <code>0.5</code> |
+  | <code>nourishing shampoo</code>      | <code>cumin lemon tea</code>           | <code>0.0</code> |
+  | <code>safe materials pacifier</code> | <code>facial serum</code>              | <code>0.5</code> |
+* Loss: [<code>CoSENTLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "pairwise_cos_sim"
+  }
+  ```
+
+### Evaluation Dataset
+
+#### pairs_three_scores_v5
+
+* Dataset: [pairs_three_scores_v5](https://huggingface.co/datasets/youssefkhalil320/pairs_three_scores_v5) at [3d8c457](https://huggingface.co/datasets/youssefkhalil320/pairs_three_scores_v5/tree/3d8c45703846bd2adfaaf422abafbc389b283de1)
+* Size: 20,000,001 evaluation samples
+* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>score</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | sentence1                                                                        | sentence2                                                                        | score                                                          |
+  |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------|
+  | type    | string                                                                           | string                                                                           | float                                                          |
+  | details | <ul><li>min: 3 tokens</li><li>mean: 6.21 tokens</li><li>max: 12 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 5.75 tokens</li><li>max: 12 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.11</li><li>max: 1.0</li></ul> |
+* Samples:
+  | sentence1                               | sentence2                          | score            |
+  |:----------------------------------------|:-----------------------------------|:-----------------|
+  | <code>teddy bear toy</code>             | <code>long lasting cat food</code> | <code>0.0</code> |
+  | <code>eva hair treatment</code>         | <code>fresh pineapple</code>       | <code>0.0</code> |
+  | <code>soft wave hair conditioner</code> | <code>hybrid seat bike</code>      | <code>0.0</code> |
+* Loss: [<code>CoSENTLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "pairwise_cos_sim"
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 128
+- `per_device_eval_batch_size`: 128
+- `learning_rate`: 2e-05
+- `num_train_epochs`: 1
+- `warmup_ratio`: 0.1
+- `fp16`: True
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 128
+- `per_device_eval_batch_size`: 128
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 1
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 2e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1.0
+- `num_train_epochs`: 1
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.1
+- `warmup_steps`: 0
+- `log_level`: passive
+- `log_level_replica`: warning
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `save_safetensors`: True
+- `save_on_each_node`: False
+- `save_only_model`: False
+- `restore_callback_states_from_checkpoint`: False
+- `no_cuda`: False
+- `use_cpu`: False
+- `use_mps_device`: False
+- `seed`: 42
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: False
+- `fp16`: True
+- `fp16_opt_level`: O1
+- `half_precision_backend`: auto
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `local_rank`: 0
+- `ddp_backend`: None
+- `tpu_num_cores`: None
+- `tpu_metrics_debug`: False
+- `debug`: []
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 0
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: False
+- `resume_from_checkpoint`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_private_repo`: False
+- `hub_always_push`: False
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`: 
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `dispatch_batches`: None
+- `split_batches`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `eval_use_gather_object`: False
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: proportional
+
+</details>
+
+### Training Logs
+<details><summary>Click to expand</summary>
+
+| Epoch  | Step  | Training Loss |
+|:------:|:-----:|:-------------:|
+| 0.0002 | 100   | 10.8792       |
+| 0.0003 | 200   | 10.9284       |
+| 0.0005 | 300   | 10.6466       |
+| 0.0006 | 400   | 10.841        |
+| 0.0008 | 500   | 10.8094       |
+| 0.0010 | 600   | 10.4323       |
+| 0.0011 | 700   | 10.3032       |
+| 0.0013 | 800   | 10.4006       |
+| 0.0014 | 900   | 10.4743       |
+| 0.0016 | 1000  | 10.2334       |
+| 0.0018 | 1100  | 10.0135       |
+| 0.0019 | 1200  | 9.7874        |
+| 0.0021 | 1300  | 9.7419        |
+| 0.0022 | 1400  | 9.7412        |
+| 0.0024 | 1500  | 9.4585        |
+| 0.0026 | 1600  | 9.5339        |
+| 0.0027 | 1700  | 9.4345        |
+| 0.0029 | 1800  | 9.1733        |
+| 0.0030 | 1900  | 8.9952        |
+| 0.0032 | 2000  | 8.9669        |
+| 0.0034 | 2100  | 8.8152        |
+| 0.0035 | 2200  | 8.7936        |
+| 0.0037 | 2300  | 8.6771        |
+| 0.0038 | 2400  | 8.4648        |
+| 0.0040 | 2500  | 8.5764        |
+| 0.0042 | 2600  | 8.4587        |
+| 0.0043 | 2700  | 8.2966        |
+| 0.0045 | 2800  | 8.2329        |
+| 0.0046 | 2900  | 8.1415        |
+| 0.0048 | 3000  | 8.0404        |
+| 0.0050 | 3100  | 7.9698        |
+| 0.0051 | 3200  | 7.9205        |
+| 0.0053 | 3300  | 7.8314        |
+| 0.0054 | 3400  | 7.8369        |
+| 0.0056 | 3500  | 7.6403        |
+| 0.0058 | 3600  | 7.5842        |
+| 0.0059 | 3700  | 7.5812        |
+| 0.0061 | 3800  | 7.4335        |
+| 0.0062 | 3900  | 7.4917        |
+| 0.0064 | 4000  | 7.3204        |
+| 0.0066 | 4100  | 7.2971        |
+| 0.0067 | 4200  | 7.2233        |
+| 0.0069 | 4300  | 7.2081        |
+| 0.0070 | 4400  | 7.1364        |
+| 0.0072 | 4500  | 7.0663        |
+| 0.0074 | 4600  | 6.9601        |
+| 0.0075 | 4700  | 6.9546        |
+| 0.0077 | 4800  | 6.9019        |
+| 0.0078 | 4900  | 6.8801        |
+| 0.0080 | 5000  | 6.7734        |
+| 0.0082 | 5100  | 6.7648        |
+| 0.0083 | 5200  | 6.7498        |
+| 0.0085 | 5300  | 6.6872        |
+| 0.0086 | 5400  | 6.6264        |
+| 0.0088 | 5500  | 6.579         |
+| 0.0090 | 5600  | 6.6001        |
+| 0.0091 | 5700  | 6.5971        |
+| 0.0093 | 5800  | 6.4694        |
+| 0.0094 | 5900  | 6.3983        |
+| 0.0096 | 6000  | 6.4477        |
+| 0.0098 | 6100  | 6.4308        |
+| 0.0099 | 6200  | 6.4248        |
+| 0.0101 | 6300  | 6.2642        |
+| 0.0102 | 6400  | 6.2763        |
+| 0.0104 | 6500  | 6.3878        |
+| 0.0106 | 6600  | 6.2601        |
+| 0.0107 | 6700  | 6.1789        |
+| 0.0109 | 6800  | 6.1773        |
+| 0.0110 | 6900  | 6.1439        |
+| 0.0112 | 7000  | 6.1863        |
+| 0.0114 | 7100  | 6.0513        |
+| 0.0115 | 7200  | 6.0671        |
+| 0.0117 | 7300  | 6.0212        |
+| 0.0118 | 7400  | 6.0043        |
+| 0.0120 | 7500  | 6.0166        |
+| 0.0122 | 7600  | 5.9754        |
+| 0.0123 | 7700  | 5.9211        |
+| 0.0125 | 7800  | 5.7867        |
+| 0.0126 | 7900  | 5.8534        |
+| 0.0128 | 8000  | 5.7708        |
+| 0.0130 | 8100  | 5.8328        |
+| 0.0131 | 8200  | 5.7417        |
+| 0.0133 | 8300  | 5.8097        |
+| 0.0134 | 8400  | 5.7578        |
+| 0.0136 | 8500  | 5.643         |
+| 0.0138 | 8600  | 5.6401        |
+| 0.0139 | 8700  | 5.6627        |
+| 0.0141 | 8800  | 5.6167        |
+| 0.0142 | 8900  | 5.6539        |
+| 0.0144 | 9000  | 5.4513        |
+| 0.0146 | 9100  | 5.4132        |
+| 0.0147 | 9200  | 5.4714        |
+| 0.0149 | 9300  | 5.4786        |
+| 0.0150 | 9400  | 5.3928        |
+| 0.0152 | 9500  | 5.4774        |
+| 0.0154 | 9600  | 5.2881        |
+| 0.0155 | 9700  | 5.3699        |
+| 0.0157 | 9800  | 5.1483        |
+| 0.0158 | 9900  | 5.3051        |
+| 0.0160 | 10000 | 5.2546        |
+| 0.0162 | 10100 | 5.2314        |
+| 0.0163 | 10200 | 5.1783        |
+| 0.0165 | 10300 | 5.2074        |
+| 0.0166 | 10400 | 5.2825        |
+| 0.0168 | 10500 | 5.1715        |
+| 0.0170 | 10600 | 5.087         |
+| 0.0171 | 10700 | 5.082         |
+| 0.0173 | 10800 | 4.9111        |
+| 0.0174 | 10900 | 5.0213        |
+| 0.0176 | 11000 | 4.9898        |
+| 0.0178 | 11100 | 4.7734        |
+| 0.0179 | 11200 | 4.9511        |
+| 0.0181 | 11300 | 5.0481        |
+| 0.0182 | 11400 | 4.8441        |
+| 0.0184 | 11500 | 4.873         |
+| 0.0186 | 11600 | 4.9988        |
+| 0.0187 | 11700 | 4.7653        |
+| 0.0189 | 11800 | 4.804         |
+| 0.0190 | 11900 | 4.8288        |
+| 0.0192 | 12000 | 4.7053        |
+| 0.0194 | 12100 | 4.6887        |
+| 0.0195 | 12200 | 4.7832        |
+| 0.0197 | 12300 | 4.6817        |
+| 0.0198 | 12400 | 4.6252        |
+| 0.0200 | 12500 | 4.5936        |
+| 0.0202 | 12600 | 4.7452        |
+| 0.0203 | 12700 | 4.5321        |
+| 0.0205 | 12800 | 4.4964        |
+| 0.0206 | 12900 | 4.4421        |
+| 0.0208 | 13000 | 4.3782        |
+| 0.0210 | 13100 | 4.5169        |
+| 0.0211 | 13200 | 4.533         |
+| 0.0213 | 13300 | 4.3725        |
+| 0.0214 | 13400 | 4.2911        |
+| 0.0216 | 13500 | 4.2261        |
+
+</details>
+
+### Framework Versions
+- Python: 3.8.10
+- Sentence Transformers: 3.1.1
+- Transformers: 4.45.2
+- PyTorch: 2.4.1+cu118
+- Accelerate: 1.0.1
+- Datasets: 3.0.1
+- Tokenizers: 0.20.3
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+#### CoSENTLoss
+```bibtex
+@online{kexuefm-8847,
+    title={CoSENT: A more efficient sentence vector scheme than Sentence-BERT},
+    author={Su Jianlin},
+    year={2022},
+    month={Jan},
+    url={https://kexue.fm/archives/8847},
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

checkpoint-13500/config.json

@@ -0,0 +1,26 @@
+{
+  "_name_or_path": "sentence-transformers/all-MiniLM-L6-v2",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.45.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

checkpoint-13500/config_sentence_transformers.json

@@ -0,0 +1,10 @@
+{
+  "__version__": {
+    "sentence_transformers": "3.1.1",
+    "transformers": "4.45.2",
+    "pytorch": "2.4.1+cu118"
+  },
+  "prompts": {},
+  "default_prompt_name": null,
+  "similarity_fn_name": null
+}

checkpoint-13500/model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9a61bdbcdf52773c76129fc9a8f4ed4e6c53c99643f38d5ab89af6e43c41e474
+size 90864192

checkpoint-13500/modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

checkpoint-13500/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8633cf6f6b184e49c694d0e445c580fc8f6023bb2ae9eebf404abafd81273940
+size 180607738

checkpoint-13500/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6eb7fa64e089c65ab646a683a958b9842d3d50f08663657a23d91a28b4d209ab
+size 14244

checkpoint-13500/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cd5e7ed8b83ef9e0a04010c2a396aa4abb3e9efe091d2709c48f6b84aea2489f
+size 1064

checkpoint-13500/sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 256,
+  "do_lower_case": false
+}

checkpoint-13500/special_tokens_map.json

@@ -0,0 +1,37 @@
+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

checkpoint-13500/tokenizer_config.json

@@ -0,0 +1,64 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "max_length": 128,
+  "model_max_length": 256,
+  "never_split": null,
+  "pad_to_multiple_of": null,
+  "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}

checkpoint-13500/trainer_state.json

@@ -0,0 +1,978 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.021599965440055297,
+  "eval_steps": 200000,
+  "global_step": 13500,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.0001599997440004096,
+      "grad_norm": 84.32501983642578,
+      "learning_rate": 3.103950336794611e-08,
+      "loss": 10.8792,
+      "step": 100
+    },
+    {
+      "epoch": 0.0003199994880008192,
+      "grad_norm": 60.63747024536133,
+      "learning_rate": 6.303899137613798e-08,
+      "loss": 10.9284,
+      "step": 200
+    },
+    {
+      "epoch": 0.00047999923200122877,
+      "grad_norm": 55.71075439453125,
+      "learning_rate": 9.503847938432986e-08,
+      "loss": 10.6466,
+      "step": 300
+    },
+    {
+      "epoch": 0.0006399989760016384,
+      "grad_norm": 57.63307189941406,
+      "learning_rate": 1.2703796739252173e-07,
+      "loss": 10.841,
+      "step": 400
+    },
+    {
+      "epoch": 0.000799998720002048,
+      "grad_norm": 89.1032485961914,
+      "learning_rate": 1.590374554007136e-07,
+      "loss": 10.8094,
+      "step": 500
+    },
+    {
+      "epoch": 0.0009599984640024575,
+      "grad_norm": 57.2479362487793,
+      "learning_rate": 1.9103694340890547e-07,
+      "loss": 10.4323,
+      "step": 600
+    },
+    {
+      "epoch": 0.0011199982080028672,
+      "grad_norm": 51.17530059814453,
+      "learning_rate": 2.2303643141709733e-07,
+      "loss": 10.3032,
+      "step": 700
+    },
+    {
+      "epoch": 0.0012799979520032767,
+      "grad_norm": 60.76409912109375,
+      "learning_rate": 2.550359194252892e-07,
+      "loss": 10.4006,
+      "step": 800
+    },
+    {
+      "epoch": 0.0014399976960036865,
+      "grad_norm": 67.00859069824219,
+      "learning_rate": 2.870354074334811e-07,
+      "loss": 10.4743,
+      "step": 900
+    },
+    {
+      "epoch": 0.001599997440004096,
+      "grad_norm": 68.4343032836914,
+      "learning_rate": 3.19034895441673e-07,
+      "loss": 10.2334,
+      "step": 1000
+    },
+    {
+      "epoch": 0.0017599971840045055,
+      "grad_norm": 48.704105377197266,
+      "learning_rate": 3.510343834498648e-07,
+      "loss": 10.0135,
+      "step": 1100
+    },
+    {
+      "epoch": 0.001919996928004915,
+      "grad_norm": 45.30134963989258,
+      "learning_rate": 3.830338714580567e-07,
+      "loss": 9.7874,
+      "step": 1200
+    },
+    {
+      "epoch": 0.002079996672005325,
+      "grad_norm": 84.56024169921875,
+      "learning_rate": 4.150333594662486e-07,
+      "loss": 9.7419,
+      "step": 1300
+    },
+    {
+      "epoch": 0.0022399964160057344,
+      "grad_norm": 45.73213195800781,
+      "learning_rate": 4.470328474744404e-07,
+      "loss": 9.7412,
+      "step": 1400
+    },
+    {
+      "epoch": 0.002399996160006144,
+      "grad_norm": 50.21996307373047,
+      "learning_rate": 4.790323354826324e-07,
+      "loss": 9.4585,
+      "step": 1500
+    },
+    {
+      "epoch": 0.0025599959040065534,
+      "grad_norm": 59.475799560546875,
+      "learning_rate": 5.110318234908241e-07,
+      "loss": 9.5339,
+      "step": 1600
+    },
+    {
+      "epoch": 0.002719995648006963,
+      "grad_norm": 82.53620910644531,
+      "learning_rate": 5.43031311499016e-07,
+      "loss": 9.4345,
+      "step": 1700
+    },
+    {
+      "epoch": 0.002879995392007373,
+      "grad_norm": 39.44235610961914,
+      "learning_rate": 5.750307995072079e-07,
+      "loss": 9.1733,
+      "step": 1800
+    },
+    {
+      "epoch": 0.0030399951360077825,
+      "grad_norm": 37.58698654174805,
+      "learning_rate": 6.070302875153998e-07,
+      "loss": 8.9952,
+      "step": 1900
+    },
+    {
+      "epoch": 0.003199994880008192,
+      "grad_norm": 40.35204315185547,
+      "learning_rate": 6.390297755235917e-07,
+      "loss": 8.9669,
+      "step": 2000
+    },
+    {
+      "epoch": 0.0033599946240086016,
+      "grad_norm": 57.84451675415039,
+      "learning_rate": 6.707092686517017e-07,
+      "loss": 8.8152,
+      "step": 2100
+    },
+    {
+      "epoch": 0.003519994368009011,
+      "grad_norm": 40.126953125,
+      "learning_rate": 7.027087566598935e-07,
+      "loss": 8.7936,
+      "step": 2200
+    },
+    {
+      "epoch": 0.0036799941120094206,
+      "grad_norm": 35.435707092285156,
+      "learning_rate": 7.347082446680854e-07,
+      "loss": 8.6771,
+      "step": 2300
+    },
+    {
+      "epoch": 0.00383999385600983,
+      "grad_norm": 42.3509635925293,
+      "learning_rate": 7.667077326762773e-07,
+      "loss": 8.4648,
+      "step": 2400
+    },
+    {
+      "epoch": 0.00399999360001024,
+      "grad_norm": 33.58556365966797,
+      "learning_rate": 7.987072206844691e-07,
+      "loss": 8.5764,
+      "step": 2500
+    },
+    {
+      "epoch": 0.00415999334401065,
+      "grad_norm": 34.014678955078125,
+      "learning_rate": 8.30706708692661e-07,
+      "loss": 8.4587,
+      "step": 2600
+    },
+    {
+      "epoch": 0.004319993088011059,
+      "grad_norm": 36.43831253051758,
+      "learning_rate": 8.627061967008528e-07,
+      "loss": 8.2966,
+      "step": 2700
+    },
+    {
+      "epoch": 0.004479992832011469,
+      "grad_norm": 31.411684036254883,
+      "learning_rate": 8.947056847090448e-07,
+      "loss": 8.2329,
+      "step": 2800
+    },
+    {
+      "epoch": 0.004639992576011879,
+      "grad_norm": 47.570125579833984,
+      "learning_rate": 9.267051727172366e-07,
+      "loss": 8.1415,
+      "step": 2900
+    },
+    {
+      "epoch": 0.004799992320012288,
+      "grad_norm": 30.771928787231445,
+      "learning_rate": 9.587046607254284e-07,
+      "loss": 8.0404,
+      "step": 3000
+    },
+    {
+      "epoch": 0.004959992064012698,
+      "grad_norm": 26.92803955078125,
+      "learning_rate": 9.907041487336204e-07,
+      "loss": 7.9698,
+      "step": 3100
+    },
+    {
+      "epoch": 0.005119991808013107,
+      "grad_norm": 31.121917724609375,
+      "learning_rate": 1.0227036367418122e-06,
+      "loss": 7.9205,
+      "step": 3200
+    },
+    {
+      "epoch": 0.005279991552013517,
+      "grad_norm": 33.991416931152344,
+      "learning_rate": 1.054703124750004e-06,
+      "loss": 7.8314,
+      "step": 3300
+    },
+    {
+      "epoch": 0.005439991296013926,
+      "grad_norm": 31.278030395507812,
+      "learning_rate": 1.086702612758196e-06,
+      "loss": 7.8369,
+      "step": 3400
+    },
+    {
+      "epoch": 0.005599991040014336,
+      "grad_norm": 28.116140365600586,
+      "learning_rate": 1.1187021007663878e-06,
+      "loss": 7.6403,
+      "step": 3500
+    },
+    {
+      "epoch": 0.005759990784014746,
+      "grad_norm": 30.954113006591797,
+      "learning_rate": 1.1507015887745798e-06,
+      "loss": 7.5842,
+      "step": 3600
+    },
+    {
+      "epoch": 0.005919990528015155,
+      "grad_norm": 36.53567886352539,
+      "learning_rate": 1.1827010767827715e-06,
+      "loss": 7.5812,
+      "step": 3700
+    },
+    {
+      "epoch": 0.006079990272015565,
+      "grad_norm": 36.81153106689453,
+      "learning_rate": 1.2147005647909635e-06,
+      "loss": 7.4335,
+      "step": 3800
+    },
+    {
+      "epoch": 0.006239990016015974,
+      "grad_norm": 22.556833267211914,
+      "learning_rate": 1.2467000527991553e-06,
+      "loss": 7.4917,
+      "step": 3900
+    },
+    {
+      "epoch": 0.006399989760016384,
+      "grad_norm": 40.195579528808594,
+      "learning_rate": 1.278699540807347e-06,
+      "loss": 7.3204,
+      "step": 4000
+    },
+    {
+      "epoch": 0.006559989504016793,
+      "grad_norm": 21.862642288208008,
+      "learning_rate": 1.310699028815539e-06,
+      "loss": 7.2971,
+      "step": 4100
+    },
+    {
+      "epoch": 0.006719989248017203,
+      "grad_norm": 29.61161231994629,
+      "learning_rate": 1.3426985168237308e-06,
+      "loss": 7.2233,
+      "step": 4200
+    },
+    {
+      "epoch": 0.006879988992017613,
+      "grad_norm": 22.342451095581055,
+      "learning_rate": 1.3746980048319228e-06,
+      "loss": 7.2081,
+      "step": 4300
+    },
+    {
+      "epoch": 0.007039988736018022,
+      "grad_norm": 36.36684799194336,
+      "learning_rate": 1.4066974928401148e-06,
+      "loss": 7.1364,
+      "step": 4400
+    },
+    {
+      "epoch": 0.007199988480018432,
+      "grad_norm": 25.563953399658203,
+      "learning_rate": 1.4386969808483064e-06,
+      "loss": 7.0663,
+      "step": 4500
+    },
+    {
+      "epoch": 0.007359988224018841,
+      "grad_norm": 22.50385856628418,
+      "learning_rate": 1.4706964688564984e-06,
+      "loss": 6.9601,
+      "step": 4600
+    },
+    {
+      "epoch": 0.007519987968019251,
+      "grad_norm": 31.61231231689453,
+      "learning_rate": 1.5026959568646904e-06,
+      "loss": 6.9546,
+      "step": 4700
+    },
+    {
+      "epoch": 0.00767998771201966,
+      "grad_norm": 18.862520217895508,
+      "learning_rate": 1.5346954448728822e-06,
+      "loss": 6.9019,
+      "step": 4800
+    },
+    {
+      "epoch": 0.00783998745602007,
+      "grad_norm": 32.594539642333984,
+      "learning_rate": 1.5666949328810741e-06,
+      "loss": 6.8801,
+      "step": 4900
+    },
+    {
+      "epoch": 0.00799998720002048,
+      "grad_norm": 21.06804084777832,
+      "learning_rate": 1.598694420889266e-06,
+      "loss": 6.7734,
+      "step": 5000
+    },
+    {
+      "epoch": 0.00815998694402089,
+      "grad_norm": 31.783803939819336,
+      "learning_rate": 1.6303739140173757e-06,
+      "loss": 6.7648,
+      "step": 5100
+    },
+    {
+      "epoch": 0.0083199866880213,
+      "grad_norm": 49.79084777832031,
+      "learning_rate": 1.6623734020255677e-06,
+      "loss": 6.7498,
+      "step": 5200
+    },
+    {
+      "epoch": 0.008479986432021708,
+      "grad_norm": 26.1977481842041,
+      "learning_rate": 1.6943728900337597e-06,
+      "loss": 6.6872,
+      "step": 5300
+    },
+    {
+      "epoch": 0.008639986176022118,
+      "grad_norm": 21.942001342773438,
+      "learning_rate": 1.7263723780419515e-06,
+      "loss": 6.6264,
+      "step": 5400
+    },
+    {
+      "epoch": 0.008799985920022528,
+      "grad_norm": 32.572959899902344,
+      "learning_rate": 1.7583718660501433e-06,
+      "loss": 6.579,
+      "step": 5500
+    },
+    {
+      "epoch": 0.008959985664022938,
+      "grad_norm": 20.728240966796875,
+      "learning_rate": 1.7903713540583353e-06,
+      "loss": 6.6001,
+      "step": 5600
+    },
+    {
+      "epoch": 0.009119985408023347,
+      "grad_norm": 24.334205627441406,
+      "learning_rate": 1.822370842066527e-06,
+      "loss": 6.5971,
+      "step": 5700
+    },
+    {
+      "epoch": 0.009279985152023757,
+      "grad_norm": 27.025753021240234,
+      "learning_rate": 1.854370330074719e-06,
+      "loss": 6.4694,
+      "step": 5800
+    },
+    {
+      "epoch": 0.009439984896024167,
+      "grad_norm": 23.506013870239258,
+      "learning_rate": 1.8863698180829106e-06,
+      "loss": 6.3983,
+      "step": 5900
+    },
+    {
+      "epoch": 0.009599984640024576,
+      "grad_norm": 35.65713882446289,
+      "learning_rate": 1.9183693060911026e-06,
+      "loss": 6.4477,
+      "step": 6000
+    },
+    {
+      "epoch": 0.009759984384024985,
+      "grad_norm": 22.977373123168945,
+      "learning_rate": 1.950368794099295e-06,
+      "loss": 6.4308,
+      "step": 6100
+    },
+    {
+      "epoch": 0.009919984128025396,
+      "grad_norm": 22.127635955810547,
+      "learning_rate": 1.982368282107486e-06,
+      "loss": 6.4248,
+      "step": 6200
+    },
+    {
+      "epoch": 0.010079983872025805,
+      "grad_norm": 33.53960418701172,
+      "learning_rate": 2.0143677701156784e-06,
+      "loss": 6.2642,
+      "step": 6300
+    },
+    {
+      "epoch": 0.010239983616026214,
+      "grad_norm": 24.39597511291504,
+      "learning_rate": 2.04636725812387e-06,
+      "loss": 6.2763,
+      "step": 6400
+    },
+    {
+      "epoch": 0.010399983360026625,
+      "grad_norm": 24.471288681030273,
+      "learning_rate": 2.078366746132062e-06,
+      "loss": 6.3878,
+      "step": 6500
+    },
+    {
+      "epoch": 0.010559983104027034,
+      "grad_norm": 34.05498123168945,
+      "learning_rate": 2.110366234140254e-06,
+      "loss": 6.2601,
+      "step": 6600
+    },
+    {
+      "epoch": 0.010719982848027443,
+      "grad_norm": 30.60455322265625,
+      "learning_rate": 2.142365722148446e-06,
+      "loss": 6.1789,
+      "step": 6700
+    },
+    {
+      "epoch": 0.010879982592027852,
+      "grad_norm": 27.737686157226562,
+      "learning_rate": 2.1743652101566377e-06,
+      "loss": 6.1773,
+      "step": 6800
+    },
+    {
+      "epoch": 0.011039982336028263,
+      "grad_norm": 24.246810913085938,
+      "learning_rate": 2.2063646981648294e-06,
+      "loss": 6.1439,
+      "step": 6900
+    },
+    {
+      "epoch": 0.011199982080028672,
+      "grad_norm": 27.53533363342285,
+      "learning_rate": 2.2383641861730217e-06,
+      "loss": 6.1863,
+      "step": 7000
+    },
+    {
+      "epoch": 0.011359981824029081,
+      "grad_norm": 27.81687355041504,
+      "learning_rate": 2.2703636741812134e-06,
+      "loss": 6.0513,
+      "step": 7100
+    },
+    {
+      "epoch": 0.011519981568029492,
+      "grad_norm": 28.00519371032715,
+      "learning_rate": 2.3020431673093234e-06,
+      "loss": 6.0671,
+      "step": 7200
+    },
+    {
+      "epoch": 0.011679981312029901,
+      "grad_norm": 29.347061157226562,
+      "learning_rate": 2.3340426553175152e-06,
+      "loss": 6.0212,
+      "step": 7300
+    },
+    {
+      "epoch": 0.01183998105603031,
+      "grad_norm": 29.621200561523438,
+      "learning_rate": 2.365722148445625e-06,
+      "loss": 6.0043,
+      "step": 7400
+    },
+    {
+      "epoch": 0.011999980800030719,
+      "grad_norm": 31.689117431640625,
+      "learning_rate": 2.397721636453817e-06,
+      "loss": 6.0166,
+      "step": 7500
+    },
+    {
+      "epoch": 0.01215998054403113,
+      "grad_norm": 46.79508972167969,
+      "learning_rate": 2.429721124462009e-06,
+      "loss": 5.9754,
+      "step": 7600
+    },
+    {
+      "epoch": 0.012319980288031539,
+      "grad_norm": 28.857833862304688,
+      "learning_rate": 2.4617206124702006e-06,
+      "loss": 5.9211,
+      "step": 7700
+    },
+    {
+      "epoch": 0.012479980032031948,
+      "grad_norm": 58.34132766723633,
+      "learning_rate": 2.4937201004783928e-06,
+      "loss": 5.7867,
+      "step": 7800
+    },
+    {
+      "epoch": 0.012639979776032359,
+      "grad_norm": 49.33425521850586,
+      "learning_rate": 2.525719588486584e-06,
+      "loss": 5.8534,
+      "step": 7900
+    },
+    {
+      "epoch": 0.012799979520032768,
+      "grad_norm": 39.17392349243164,
+      "learning_rate": 2.5577190764947763e-06,
+      "loss": 5.7708,
+      "step": 8000
+    },
+    {
+      "epoch": 0.012959979264033177,
+      "grad_norm": 45.94136428833008,
+      "learning_rate": 2.589718564502968e-06,
+      "loss": 5.8328,
+      "step": 8100
+    },
+    {
+      "epoch": 0.013119979008033586,
+      "grad_norm": 36.19196319580078,
+      "learning_rate": 2.6217180525111603e-06,
+      "loss": 5.7417,
+      "step": 8200
+    },
+    {
+      "epoch": 0.013279978752033997,
+      "grad_norm": 37.051658630371094,
+      "learning_rate": 2.653717540519352e-06,
+      "loss": 5.8097,
+      "step": 8300
+    },
+    {
+      "epoch": 0.013439978496034406,
+      "grad_norm": 90.0757064819336,
+      "learning_rate": 2.6857170285275435e-06,
+      "loss": 5.7578,
+      "step": 8400
+    },
+    {
+      "epoch": 0.013599978240034815,
+      "grad_norm": 92.7857894897461,
+      "learning_rate": 2.7177165165357357e-06,
+      "loss": 5.643,
+      "step": 8500
+    },
+    {
+      "epoch": 0.013759977984035226,
+      "grad_norm": 26.648149490356445,
+      "learning_rate": 2.7497160045439274e-06,
+      "loss": 5.6401,
+      "step": 8600
+    },
+    {
+      "epoch": 0.013919977728035635,
+      "grad_norm": 45.42919158935547,
+      "learning_rate": 2.7817154925521196e-06,
+      "loss": 5.6627,
+      "step": 8700
+    },
+    {
+      "epoch": 0.014079977472036044,
+      "grad_norm": 48.3182487487793,
+      "learning_rate": 2.8137149805603114e-06,
+      "loss": 5.6167,
+      "step": 8800
+    },
+    {
+      "epoch": 0.014239977216036454,
+      "grad_norm": 51.463653564453125,
+      "learning_rate": 2.8457144685685028e-06,
+      "loss": 5.6539,
+      "step": 8900
+    },
+    {
+      "epoch": 0.014399976960036864,
+      "grad_norm": 47.81680679321289,
+      "learning_rate": 2.877713956576695e-06,
+      "loss": 5.4513,
+      "step": 9000
+    },
+    {
+      "epoch": 0.014559976704037273,
+      "grad_norm": 42.410667419433594,
+      "learning_rate": 2.9097134445848868e-06,
+      "loss": 5.4132,
+      "step": 9100
+    },
+    {
+      "epoch": 0.014719976448037683,
+      "grad_norm": 55.33562088012695,
+      "learning_rate": 2.941712932593079e-06,
+      "loss": 5.4714,
+      "step": 9200
+    },
+    {
+      "epoch": 0.014879976192038093,
+      "grad_norm": 38.538246154785156,
+      "learning_rate": 2.9737124206012707e-06,
+      "loss": 5.4786,
+      "step": 9300
+    },
+    {
+      "epoch": 0.015039975936038502,
+      "grad_norm": 43.42023468017578,
+      "learning_rate": 3.0057119086094625e-06,
+      "loss": 5.3928,
+      "step": 9400
+    },
+    {
+      "epoch": 0.015199975680038912,
+      "grad_norm": 24.861467361450195,
+      "learning_rate": 3.037391401737572e-06,
+      "loss": 5.4774,
+      "step": 9500
+    },
+    {
+      "epoch": 0.01535997542403932,
+      "grad_norm": 98.92141723632812,
+      "learning_rate": 3.0693908897457643e-06,
+      "loss": 5.2881,
+      "step": 9600
+    },
+    {
+      "epoch": 0.015519975168039732,
+      "grad_norm": 62.839866638183594,
+      "learning_rate": 3.101390377753956e-06,
+      "loss": 5.3699,
+      "step": 9700
+    },
+    {
+      "epoch": 0.01567997491204014,
+      "grad_norm": 46.006065368652344,
+      "learning_rate": 3.133069870882066e-06,
+      "loss": 5.1483,
+      "step": 9800
+    },
+    {
+      "epoch": 0.01583997465604055,
+      "grad_norm": 89.62445068359375,
+      "learning_rate": 3.1650693588902583e-06,
+      "loss": 5.3051,
+      "step": 9900
+    },
+    {
+      "epoch": 0.01599997440004096,
+      "grad_norm": 41.113609313964844,
+      "learning_rate": 3.19706884689845e-06,
+      "loss": 5.2546,
+      "step": 10000
+    },
+    {
+      "epoch": 0.01615997414404137,
+      "grad_norm": 46.37376403808594,
+      "learning_rate": 3.2290683349066414e-06,
+      "loss": 5.2314,
+      "step": 10100
+    },
+    {
+      "epoch": 0.01631997388804178,
+      "grad_norm": 60.3846321105957,
+      "learning_rate": 3.2610678229148337e-06,
+      "loss": 5.1783,
+      "step": 10200
+    },
+    {
+      "epoch": 0.016479973632042188,
+      "grad_norm": 145.4359130859375,
+      "learning_rate": 3.2930673109230254e-06,
+      "loss": 5.2074,
+      "step": 10300
+    },
+    {
+      "epoch": 0.0166399733760426,
+      "grad_norm": 69.00183868408203,
+      "learning_rate": 3.325066798931217e-06,
+      "loss": 5.2825,
+      "step": 10400
+    },
+    {
+      "epoch": 0.01679997312004301,
+      "grad_norm": 48.03580093383789,
+      "learning_rate": 3.3570662869394094e-06,
+      "loss": 5.1715,
+      "step": 10500
+    },
+    {
+      "epoch": 0.016959972864043417,
+      "grad_norm": 58.56736755371094,
+      "learning_rate": 3.389065774947601e-06,
+      "loss": 5.087,
+      "step": 10600
+    },
+    {
+      "epoch": 0.017119972608043828,
+      "grad_norm": 54.484527587890625,
+      "learning_rate": 3.421065262955793e-06,
+      "loss": 5.082,
+      "step": 10700
+    },
+    {
+      "epoch": 0.017279972352044235,
+      "grad_norm": 74.30866241455078,
+      "learning_rate": 3.4530647509639847e-06,
+      "loss": 4.9111,
+      "step": 10800
+    },
+    {
+      "epoch": 0.017439972096044646,
+      "grad_norm": 60.489505767822266,
+      "learning_rate": 3.4850642389721765e-06,
+      "loss": 5.0213,
+      "step": 10900
+    },
+    {
+      "epoch": 0.017599971840045057,
+      "grad_norm": 61.25093460083008,
+      "learning_rate": 3.5170637269803687e-06,
+      "loss": 4.9898,
+      "step": 11000
+    },
+    {
+      "epoch": 0.017759971584045464,
+      "grad_norm": 51.98568344116211,
+      "learning_rate": 3.5490632149885605e-06,
+      "loss": 4.7734,
+      "step": 11100
+    },
+    {
+      "epoch": 0.017919971328045875,
+      "grad_norm": 64.08167266845703,
+      "learning_rate": 3.581062702996752e-06,
+      "loss": 4.9511,
+      "step": 11200
+    },
+    {
+      "epoch": 0.018079971072046286,
+      "grad_norm": 61.8354606628418,
+      "learning_rate": 3.613062191004944e-06,
+      "loss": 5.0481,
+      "step": 11300
+    },
+    {
+      "epoch": 0.018239970816046693,
+      "grad_norm": 97.53675842285156,
+      "learning_rate": 3.645061679013136e-06,
+      "loss": 4.8441,
+      "step": 11400
+    },
+    {
+      "epoch": 0.018399970560047104,
+      "grad_norm": 49.35017013549805,
+      "learning_rate": 3.677061167021328e-06,
+      "loss": 4.873,
+      "step": 11500
+    },
+    {
+      "epoch": 0.018559970304047515,
+      "grad_norm": 44.33409118652344,
+      "learning_rate": 3.70906065502952e-06,
+      "loss": 4.9988,
+      "step": 11600
+    },
+    {
+      "epoch": 0.018719970048047922,
+      "grad_norm": 140.5505828857422,
+      "learning_rate": 3.741060143037712e-06,
+      "loss": 4.7653,
+      "step": 11700
+    },
+    {
+      "epoch": 0.018879969792048333,
+      "grad_norm": 68.21163177490234,
+      "learning_rate": 3.7730596310459034e-06,
+      "loss": 4.804,
+      "step": 11800
+    },
+    {
+      "epoch": 0.019039969536048744,
+      "grad_norm": 48.678226470947266,
+      "learning_rate": 3.805059119054095e-06,
+      "loss": 4.8288,
+      "step": 11900
+    },
+    {
+      "epoch": 0.01919996928004915,
+      "grad_norm": 76.32611083984375,
+      "learning_rate": 3.837058607062287e-06,
+      "loss": 4.7053,
+      "step": 12000
+    },
+    {
+      "epoch": 0.019359969024049562,
+      "grad_norm": 70.85586547851562,
+      "learning_rate": 3.869058095070479e-06,
+      "loss": 4.6887,
+      "step": 12100
+    },
+    {
+      "epoch": 0.01951996876804997,
+      "grad_norm": 66.46036529541016,
+      "learning_rate": 3.901057583078671e-06,
+      "loss": 4.7832,
+      "step": 12200
+    },
+    {
+      "epoch": 0.01967996851205038,
+      "grad_norm": 165.13221740722656,
+      "learning_rate": 3.9330570710868636e-06,
+      "loss": 4.6817,
+      "step": 12300
+    },
+    {
+      "epoch": 0.01983996825605079,
+      "grad_norm": 118.48895263671875,
+      "learning_rate": 3.965056559095055e-06,
+      "loss": 4.6252,
+      "step": 12400
+    },
+    {
+      "epoch": 0.0199999680000512,
+      "grad_norm": 64.3436050415039,
+      "learning_rate": 3.997056047103246e-06,
+      "loss": 4.5936,
+      "step": 12500
+    },
+    {
+      "epoch": 0.02015996774405161,
+      "grad_norm": 42.27592468261719,
+      "learning_rate": 4.0290555351114385e-06,
+      "loss": 4.7452,
+      "step": 12600
+    },
+    {
+      "epoch": 0.02031996748805202,
+      "grad_norm": 60.829036712646484,
+      "learning_rate": 4.061055023119631e-06,
+      "loss": 4.5321,
+      "step": 12700
+    },
+    {
+      "epoch": 0.020479967232052428,
+      "grad_norm": 161.975830078125,
+      "learning_rate": 4.093054511127823e-06,
+      "loss": 4.4964,
+      "step": 12800
+    },
+    {
+      "epoch": 0.02063996697605284,
+      "grad_norm": 99.2963638305664,
+      "learning_rate": 4.125053999136014e-06,
+      "loss": 4.4421,
+      "step": 12900
+    },
+    {
+      "epoch": 0.02079996672005325,
+      "grad_norm": 68.78880310058594,
+      "learning_rate": 4.156733492264124e-06,
+      "loss": 4.3782,
+      "step": 13000
+    },
+    {
+      "epoch": 0.020959966464053657,
+      "grad_norm": 80.74951171875,
+      "learning_rate": 4.188732980272316e-06,
+      "loss": 4.5169,
+      "step": 13100
+    },
+    {
+      "epoch": 0.021119966208054067,
+      "grad_norm": 157.87254333496094,
+      "learning_rate": 4.220412473400426e-06,
+      "loss": 4.533,
+      "step": 13200
+    },
+    {
+      "epoch": 0.02127996595205448,
+      "grad_norm": 148.68331909179688,
+      "learning_rate": 4.252411961408618e-06,
+      "loss": 4.3725,
+      "step": 13300
+    },
+    {
+      "epoch": 0.021439965696054886,
+      "grad_norm": 72.9531021118164,
+      "learning_rate": 4.28441144941681e-06,
+      "loss": 4.2911,
+      "step": 13400
+    },
+    {
+      "epoch": 0.021599965440055297,
+      "grad_norm": 73.24847412109375,
+      "learning_rate": 4.316410937425001e-06,
+      "loss": 4.2261,
+      "step": 13500
+    }
+  ],
+  "logging_steps": 100,
+  "max_steps": 625001,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 1,
+  "save_steps": 500,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 0.0,
+  "train_batch_size": 128,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-13500/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:14eb8a69d6ba5b2bb8d2148b585526b13da2e45effc438997c1d2d513d64b838
+size 5496