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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,72 @@
+---
+base_model: meta-llama/Meta-Llama-3-8B-Instruct
+datasets:
+- princeton-nlp/llama3-ultrafeedback
+library_name: transformers
+model_name: meta-llama/Meta-Llama-3-8B-Instruct
+tags:
+- generated_from_trainer
+- simpo
+- trl
+- alignment-handbook
+licence: license
+---
+
+# Model Card for meta-llama/Meta-Llama-3-8B-Instruct
+
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the [['princeton-nlp/llama3-ultrafeedback']](https://huggingface.co/datasets/['princeton-nlp/llama3-ultrafeedback']) dataset.
+It has been trained using [TRL](https://github.com/huggingface/trl).
+
+## Quick start
+
+```python
+from transformers import pipeline
+
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="None", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/boko0128/huggingface/runs/8l9cwajh) 
+
+
+This model was trained with Pro-DPO.
+
+### Framework versions
+
+- TRL: 0.19.1
+- Transformers: 4.53.2
+- Pytorch: 2.4.0+cu121
+- Datasets: 3.6.0
+- Tokenizers: 0.21.2
+
+## Citations
+
+Cite Pro-DPO as:
+
+```bibtex
+@inproceedings{xu2024contrastive,
+    title        = {{Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation}},
+    author       = {Haoran Xu and Amr Sharaf and Yunmo Chen and Weiting Tan and Lingfeng Shen and Benjamin Van Durme and Kenton Murray and Young Jin Kim},
+    year         = 2024,
+    booktitle    = {Forty-first International Conference on Machine Learning, {ICML} 2024, Vienna, Austria, July 21-27, 2024},
+    publisher    = {OpenReview.net},
+    url          = {https://openreview.net/forum?id=51iwkioZpn}
+}
+```
+
+Cite TRL as:
+    
+```bibtex
+@misc{vonwerra2022trl,
+	title        = {{TRL: Transformer Reinforcement Learning}},
+	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```

all_results.json

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+    "eval_loss": 1.1963940858840942,
+    "eval_nll_loss": 0.0,
+    "eval_rewards/accuracies": 0.6251680254936218,
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+    "eval_rewards/margins": 0.32764163613319397,
+    "eval_rewards/rejected": -1.4110382795333862,
+    "eval_runtime": 26.5134,
+    "eval_samples": 1961,
+    "eval_samples_per_second": 73.963,
+    "eval_steps_per_second": 2.338,
+    "total_flos": 0.0,
+    "train_loss": 1.2459888947315705,
+    "train_runtime": 3192.5713,
+    "train_samples": 59876,
+    "train_samples_per_second": 18.755,
+    "train_steps_per_second": 0.147
+}

chat_template.jinja

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+{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>
+
+'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>
+
+' }}{% endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
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+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.53.2",
+  "use_cache": true,
+  "vocab_size": 128256
+}

eval_results.json

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+    "eval_rewards/margins": 0.32764163613319397,
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+    "eval_samples_per_second": 73.963,
+    "eval_steps_per_second": 2.338
+}

generation_config.json

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+  "bos_token_id": 128000,
+  "eos_token_id": [
+    128001,
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+  ],
+  "transformers_version": "4.53.2"
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