botways/llama_cpo_finetune
Browse files- README.md +67 -0
- adapter_config.json +33 -0
- adapter_model.safetensors +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer_config.json +43 -0
- trainer_state.json +90 -0
- training_args.bin +3 -0
README.md
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---
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library_name: transformers
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model_name: llama-CPO
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tags:
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- generated_from_trainer
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- trl
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- cpo
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licence: license
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---
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# Model Card for llama-CPO
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This model is a fine-tuned version of [None](https://huggingface.co/None).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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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?"
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generator = pipeline("text-generation", model="botways/llama-CPO", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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This model was trained with CPO, a method introduced in [Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation](https://huggingface.co/papers/2401.08417).
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### Framework versions
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- TRL: 0.12.1
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- Transformers: 4.46.3
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- Pytorch: 2.5.1
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- Datasets: 3.1.0
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- Tokenizers: 0.20.3
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## Citations
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Cite CPO as:
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```bibtex
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@inproceedings{xu2024contrastive,
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title = {{Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation}},
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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},
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year = 2024,
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booktitle = {Forty-first International Conference on Machine Learning, {ICML} 2024, Vienna, Austria, July 21-27, 2024},
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publisher = {OpenReview.net},
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url = {https://openreview.net/forum?id=51iwkioZpn}
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}
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```
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Cite TRL as:
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```bibtex
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@misc{vonwerra2022trl,
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title = {{TRL: Transformer Reinforcement Learning}},
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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 Gallouédec},
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year = 2020,
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journal = {GitHub repository},
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publisher = {GitHub},
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howpublished = {\url{https://github.com/huggingface/trl}}
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}
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```
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "model",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 16,
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"lora_dropout": 0.1,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 64,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"v_proj",
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"up_proj",
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"k_proj",
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"gate_proj",
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"down_proj",
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"q_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:582281102245dc527b595361d724185f2149e40472dc5f25be7b1f3e03a31ccb
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size 572574272
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "</s>",
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"add_prefix_space": null,
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"added_tokens_decoder": {
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"0": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "<s>",
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"chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\\n' + system_message + '\\n<</SYS>>\\n\\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}",
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"clean_up_tokenization_spaces": false,
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"eos_token": "</s>",
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"legacy": false,
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "</s>",
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"padding_side": "right",
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"sp_model_kwargs": {},
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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}
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trainer_state.json
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{
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"best_metric": null,
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"best_model_checkpoint": null,
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"epoch": 3.0,
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| 5 |
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"eval_steps": 500,
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| 6 |
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"global_step": 39,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"log_history": [
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{
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"epoch": 0.7692307692307693,
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| 13 |
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"grad_norm": 1.8173785209655762,
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| 14 |
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"learning_rate": 7.435897435897435e-07,
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| 15 |
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"logits/chosen": 0.13414913415908813,
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"logits/rejected": 0.12645891308784485,
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| 17 |
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"logps/chosen": -298.76983642578125,
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| 18 |
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"logps/rejected": -261.02435302734375,
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| 19 |
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"loss": 9.7803,
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| 20 |
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"nll_loss": 1.0939728021621704,
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| 21 |
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"rewards/accuracies": 0.44999998807907104,
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| 22 |
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"rewards/chosen": -29.87698745727539,
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| 23 |
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"rewards/margins": -3.774548292160034,
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| 24 |
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"rewards/rejected": -26.102436065673828,
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| 25 |
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"step": 10
|
| 26 |
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},
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| 27 |
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{
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| 28 |
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"epoch": 1.5384615384615383,
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| 29 |
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"grad_norm": 1.8889318704605103,
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"learning_rate": 4.871794871794871e-07,
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"logps/rejected": -260.14141845703125,
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"loss": 8.6446,
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"nll_loss": 1.0915288925170898,
|
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"rewards/accuracies": 0.4749999940395355,
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"rewards/chosen": -27.7278995513916,
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"rewards/margins": -1.7137558460235596,
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"rewards/rejected": -26.014141082763672,
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| 41 |
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"step": 20
|
| 42 |
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},
|
| 43 |
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{
|
| 44 |
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"epoch": 2.3076923076923075,
|
| 45 |
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"grad_norm": 1.609092354774475,
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"learning_rate": 2.3076923076923078e-07,
|
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"logits/chosen": 0.09378460794687271,
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| 48 |
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"logits/rejected": 0.0867479220032692,
|
| 49 |
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"logps/chosen": -280.64697265625,
|
| 50 |
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"logps/rejected": -273.1399841308594,
|
| 51 |
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"loss": 7.8556,
|
| 52 |
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"nll_loss": 1.1089527606964111,
|
| 53 |
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"rewards/accuracies": 0.5,
|
| 54 |
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"rewards/chosen": -28.064701080322266,
|
| 55 |
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"rewards/margins": -0.7507012486457825,
|
| 56 |
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"rewards/rejected": -27.31399917602539,
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| 57 |
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"step": 30
|
| 58 |
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},
|
| 59 |
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{
|
| 60 |
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"epoch": 3.0,
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| 61 |
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"step": 39,
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| 62 |
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"total_flos": 0.0,
|
| 63 |
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"train_loss": 8.851261627979767,
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| 64 |
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"train_runtime": 435.0584,
|
| 65 |
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"train_samples_per_second": 0.69,
|
| 66 |
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"train_steps_per_second": 0.09
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| 67 |
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}
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| 68 |
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],
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| 69 |
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"logging_steps": 10,
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| 70 |
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"max_steps": 39,
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| 71 |
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"num_input_tokens_seen": 0,
|
| 72 |
+
"num_train_epochs": 3,
|
| 73 |
+
"save_steps": 500,
|
| 74 |
+
"stateful_callbacks": {
|
| 75 |
+
"TrainerControl": {
|
| 76 |
+
"args": {
|
| 77 |
+
"should_epoch_stop": false,
|
| 78 |
+
"should_evaluate": false,
|
| 79 |
+
"should_log": false,
|
| 80 |
+
"should_save": true,
|
| 81 |
+
"should_training_stop": true
|
| 82 |
+
},
|
| 83 |
+
"attributes": {}
|
| 84 |
+
}
|
| 85 |
+
},
|
| 86 |
+
"total_flos": 0.0,
|
| 87 |
+
"train_batch_size": 8,
|
| 88 |
+
"trial_name": null,
|
| 89 |
+
"trial_params": null
|
| 90 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8b5786356a82264536514208a1f3b3612cb7f48f7f87a70601536c758e745411
|
| 3 |
+
size 5624
|