Upload folder using huggingface_hub

checkpoint-2500/1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 768,
+  "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-2500/README.md

@@ -0,0 +1,358 @@
+---
+base_model: sentence-transformers/all-mpnet-base-v2
+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:1363306
+- loss:AnglELoss
+widget:
+- source_sentence: labneh
+  sentences:
+  - iftar
+  - bathing suit
+  - coffee cup
+- source_sentence: Velvet flock Veil
+  sentences:
+  - mermaid purse
+  - veil
+  - mobile bag
+- source_sentence: Red lipstick
+  sentences:
+  - chemise dress
+  - tote
+  - rouge
+- source_sentence: Unisex Travel bag
+  sentences:
+  - spf
+  - basic vega ring
+  - travel backpack
+- source_sentence: jeremy hush book
+  sentences:
+  - chinese jumper
+  - perfume
+  - home automation device
+---
+
+# all-mpnet-base-v3-pair_score
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2). It maps sentences & paragraphs to a 768-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-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) <!-- at revision 9a3225965996d404b775526de6dbfe85d3368642 -->
+- **Maximum Sequence Length:** 384 tokens
+- **Output Dimensionality:** 768 tokens
+- **Similarity Function:** Cosine Similarity
+<!-- - **Training Dataset:** Unknown -->
+- **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': 384, 'do_lower_case': False}) with Transformer model: MPNetModel 
+  (1): Pooling({'word_embedding_dimension': 768, '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 = [
+    'jeremy hush book',
+    'chinese jumper',
+    'perfume',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 768]
+
+# 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 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`: 2
+- `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`: 2
+- `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
+| Epoch  | Step | Training Loss |
+|:------:|:----:|:-------------:|
+| 0.0094 | 100  | 16.2337       |
+| 0.0188 | 200  | 13.5901       |
+| 0.0282 | 300  | 9.8565        |
+| 0.0376 | 400  | 8.3332        |
+| 0.0469 | 500  | 8.1261        |
+| 0.0563 | 600  | 8.0697        |
+| 0.0657 | 700  | 8.0298        |
+| 0.0751 | 800  | 8.033         |
+| 0.0845 | 900  | 7.9858        |
+| 0.0939 | 1000 | 8.012         |
+| 0.1033 | 1100 | 7.9745        |
+| 0.1127 | 1200 | 8.0091        |
+| 0.1221 | 1300 | 8.0221        |
+| 0.1314 | 1400 | 7.9583        |
+| 0.1408 | 1500 | 8.0031        |
+| 0.1502 | 1600 | 7.9985        |
+| 0.1596 | 1700 | 7.9647        |
+| 0.1690 | 1800 | 7.9857        |
+| 0.1784 | 1900 | 7.9806        |
+| 0.1878 | 2000 | 7.9761        |
+| 0.1972 | 2100 | 7.9696        |
+| 0.2066 | 2200 | 8.0014        |
+| 0.2159 | 2300 | 7.9546        |
+| 0.2253 | 2400 | 7.9874        |
+| 0.2347 | 2500 | 7.9846        |
+
+
+### 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",
+}
+```
+
+#### AnglELoss
+```bibtex
+@misc{li2023angleoptimized,
+    title={AnglE-optimized Text Embeddings},
+    author={Xianming Li and Jing Li},
+    year={2023},
+    eprint={2309.12871},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+<!--
+## 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-2500/config.json

@@ -0,0 +1,24 @@
+{
+  "_name_or_path": "sentence-transformers/all-mpnet-base-v2",
+  "architectures": [
+    "MPNetModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "mpnet",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "relative_attention_num_buckets": 32,
+  "torch_dtype": "float32",
+  "transformers_version": "4.45.2",
+  "vocab_size": 30527
+}

checkpoint-2500/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-2500/model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9735ec331b62163b6392b5c105ec51ebd8362dd78001317c3576c7430efd3a6e
+size 437967672

checkpoint-2500/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-2500/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b686972473ae333eccf6f85e723bc24a5ae48b41832a5ab632a9a9a66d796500
+size 871331770

checkpoint-2500/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:90b464171ac5b0f2c24cc16f8ca89e3b78f7d6d9d5f80b5518a0ea3ca17cc564
+size 14244

checkpoint-2500/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:369dbe7ad7b364b67a78a58cfd770b81c990376900ec29e3d002dd22e99e8c29
+size 1064

checkpoint-2500/sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 384,
+  "do_lower_case": false
+}

checkpoint-2500/special_tokens_map.json

@@ -0,0 +1,51 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

checkpoint-2500/tokenizer_config.json

@@ -0,0 +1,72 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "104": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "30526": {
+      "content": "<mask>",
+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "<s>",
+  "do_lower_case": true,
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "max_length": 128,
+  "model_max_length": 384,
+  "pad_to_multiple_of": null,
+  "pad_token": "<pad>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "</s>",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "MPNetTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}

checkpoint-2500/trainer_state.json

@@ -0,0 +1,208 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.23471974462491785,
+  "eval_steps": 5000,
+  "global_step": 2500,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.009388789784996713,
+      "grad_norm": 87.77811431884766,
+      "learning_rate": 9.009854528390429e-07,
+      "loss": 16.2337,
+      "step": 100
+    },
+    {
+      "epoch": 0.018777579569993427,
+      "grad_norm": 85.86430358886719,
+      "learning_rate": 1.8395119662130456e-06,
+      "loss": 13.5901,
+      "step": 200
+    },
+    {
+      "epoch": 0.02816636935499014,
+      "grad_norm": 14.885255813598633,
+      "learning_rate": 2.7592679493195683e-06,
+      "loss": 9.8565,
+      "step": 300
+    },
+    {
+      "epoch": 0.03755515913998685,
+      "grad_norm": 6.9691972732543945,
+      "learning_rate": 3.6977944626935713e-06,
+      "loss": 8.3332,
+      "step": 400
+    },
+    {
+      "epoch": 0.04694394892498357,
+      "grad_norm": 5.612818241119385,
+      "learning_rate": 4.6363209760675744e-06,
+      "loss": 8.1261,
+      "step": 500
+    },
+    {
+      "epoch": 0.05633273870998028,
+      "grad_norm": 4.705409526824951,
+      "learning_rate": 5.574847489441577e-06,
+      "loss": 8.0697,
+      "step": 600
+    },
+    {
+      "epoch": 0.06572152849497699,
+      "grad_norm": 4.337332725524902,
+      "learning_rate": 6.51337400281558e-06,
+      "loss": 8.0298,
+      "step": 700
+    },
+    {
+      "epoch": 0.0751103182799737,
+      "grad_norm": 3.6314213275909424,
+      "learning_rate": 7.451900516189583e-06,
+      "loss": 8.033,
+      "step": 800
+    },
+    {
+      "epoch": 0.08449910806497042,
+      "grad_norm": 3.4845075607299805,
+      "learning_rate": 8.390427029563585e-06,
+      "loss": 7.9858,
+      "step": 900
+    },
+    {
+      "epoch": 0.09388789784996714,
+      "grad_norm": 5.188210487365723,
+      "learning_rate": 9.328953542937589e-06,
+      "loss": 8.012,
+      "step": 1000
+    },
+    {
+      "epoch": 0.10327668763496385,
+      "grad_norm": 3.0830442905426025,
+      "learning_rate": 1.0267480056311592e-05,
+      "loss": 7.9745,
+      "step": 1100
+    },
+    {
+      "epoch": 0.11266547741996057,
+      "grad_norm": 3.4729278087615967,
+      "learning_rate": 1.1206006569685594e-05,
+      "loss": 8.0091,
+      "step": 1200
+    },
+    {
+      "epoch": 0.12205426720495728,
+      "grad_norm": 2.329235076904297,
+      "learning_rate": 1.2144533083059597e-05,
+      "loss": 8.0221,
+      "step": 1300
+    },
+    {
+      "epoch": 0.13144305698995398,
+      "grad_norm": 2.7225279808044434,
+      "learning_rate": 1.3083059596433601e-05,
+      "loss": 7.9583,
+      "step": 1400
+    },
+    {
+      "epoch": 0.1408318467749507,
+      "grad_norm": 2.012805938720703,
+      "learning_rate": 1.4021586109807603e-05,
+      "loss": 8.0031,
+      "step": 1500
+    },
+    {
+      "epoch": 0.1502206365599474,
+      "grad_norm": 2.9397523403167725,
+      "learning_rate": 1.4960112623181606e-05,
+      "loss": 7.9985,
+      "step": 1600
+    },
+    {
+      "epoch": 0.15960942634494413,
+      "grad_norm": 2.356337308883667,
+      "learning_rate": 1.589863913655561e-05,
+      "loss": 7.9647,
+      "step": 1700
+    },
+    {
+      "epoch": 0.16899821612994084,
+      "grad_norm": 2.6846818923950195,
+      "learning_rate": 1.6837165649929613e-05,
+      "loss": 7.9857,
+      "step": 1800
+    },
+    {
+      "epoch": 0.17838700591493756,
+      "grad_norm": 2.0188565254211426,
+      "learning_rate": 1.7775692163303613e-05,
+      "loss": 7.9806,
+      "step": 1900
+    },
+    {
+      "epoch": 0.18777579569993427,
+      "grad_norm": 4.030488014221191,
+      "learning_rate": 1.8714218676677617e-05,
+      "loss": 7.9761,
+      "step": 2000
+    },
+    {
+      "epoch": 0.197164585484931,
+      "grad_norm": 4.183101654052734,
+      "learning_rate": 1.965274519005162e-05,
+      "loss": 7.9696,
+      "step": 2100
+    },
+    {
+      "epoch": 0.2065533752699277,
+      "grad_norm": 1.4769889116287231,
+      "learning_rate": 1.9934275728965626e-05,
+      "loss": 8.0014,
+      "step": 2200
+    },
+    {
+      "epoch": 0.21594216505492442,
+      "grad_norm": 2.1914358139038086,
+      "learning_rate": 1.9829951489228525e-05,
+      "loss": 7.9546,
+      "step": 2300
+    },
+    {
+      "epoch": 0.22533095483992113,
+      "grad_norm": 22.55516815185547,
+      "learning_rate": 1.972562724949142e-05,
+      "loss": 7.9874,
+      "step": 2400
+    },
+    {
+      "epoch": 0.23471974462491785,
+      "grad_norm": 1.635116457939148,
+      "learning_rate": 1.962130300975432e-05,
+      "loss": 7.9846,
+      "step": 2500
+    }
+  ],
+  "logging_steps": 100,
+  "max_steps": 21302,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 2,
+  "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-2500/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:006196a6760605807ae7aab04b3ff5762b98610dc83070d5ff9eb10989362210
+size 5496