End of training
Browse files- README.md +17 -10
- all_results.json +12 -12
- config.json +1 -1
- eval_results.json +13 -13
- runs/Sep29_22-34-07_action-graph-trainer/events.out.tfevents.1727656053.action-graph-trainer.718565.1 +3 -0
README.md
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license: llama3.2
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base_model: tanliboy/llama-3.2-3b-sft
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tags:
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- trl
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- dpo
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- alignment-handbook
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- generated_from_trainer
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model-index:
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- name: llama-3.2-3b-dpo
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results: []
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@@ -17,17 +24,17 @@ should probably proofread and complete it, then remove this comment. -->
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# llama-3.2-3b-dpo
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This model is a fine-tuned version of [tanliboy/llama-3.2-3b-sft](https://huggingface.co/tanliboy/llama-3.2-3b-sft) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Rewards/chosen: 0.
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- Rewards/rejected: -3.
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- Rewards/accuracies: 0.
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- Rewards/margins: 4.
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- Logps/rejected: -
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- Logps/chosen: -
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- Logits/rejected: 0.
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- Logits/chosen: 0.
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## Model description
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license: llama3.2
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base_model: tanliboy/llama-3.2-3b-sft
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tags:
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- alignment-handbook
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- trl
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- dpo
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- generated_from_trainer
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- trl
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- dpo
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- alignment-handbook
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- generated_from_trainer
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datasets:
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- HuggingFaceH4/orca_dpo_pairs
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- HuggingFaceH4/ultrafeedback_binarized
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model-index:
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- name: llama-3.2-3b-dpo
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results: []
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# llama-3.2-3b-dpo
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This model is a fine-tuned version of [tanliboy/llama-3.2-3b-sft](https://huggingface.co/tanliboy/llama-3.2-3b-sft) on the HuggingFaceH4/orca_dpo_pairs and the HuggingFaceH4/ultrafeedback_binarized datasets.
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It achieves the following results on the evaluation set:
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- Loss: 0.6289
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- Rewards/chosen: 0.7479
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- Rewards/rejected: -3.8379
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- Rewards/accuracies: 0.7405
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- Rewards/margins: 4.5857
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- Logps/rejected: -370.2327
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- Logps/chosen: -338.3392
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- Logits/rejected: 0.4475
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- Logits/chosen: 0.3731
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## Model description
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all_results.json
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{
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"epoch": 3.0,
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"eval_logits/chosen": 0.
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"eval_logits/rejected": 0.
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"eval_logps/rejected": -
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"eval_loss": 0.
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"eval_rewards/accuracies": 0.
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"eval_rewards/chosen":
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"eval_rewards/margins":
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"eval_rewards/rejected": -
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"eval_runtime":
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"eval_samples": 2500,
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"eval_samples_per_second":
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"eval_steps_per_second": 1.
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"total_flos": 0.0,
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"train_loss": 0.5009220597491634,
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"train_runtime": 6227.6413,
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{
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"epoch": 3.0,
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"eval_logits/chosen": 0.3730663061141968,
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"eval_logits/rejected": 0.4475269019603729,
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"eval_logps/chosen": -338.3392028808594,
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"eval_logps/rejected": -370.232666015625,
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"eval_loss": 0.6289177536964417,
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"eval_rewards/accuracies": 0.7405063509941101,
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"eval_rewards/chosen": 0.7478683590888977,
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"eval_rewards/margins": 4.585729122161865,
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"eval_rewards/rejected": -3.8378612995147705,
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"eval_runtime": 70.1775,
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"eval_samples": 2500,
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"eval_samples_per_second": 35.624,
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"eval_steps_per_second": 1.126,
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"total_flos": 0.0,
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"train_loss": 0.5009220597491634,
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"train_runtime": 6227.6413,
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config.json
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"tie_word_embeddings": true,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.44.2",
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"use_cache":
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"vocab_size": 128256
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}
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"tie_word_embeddings": true,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.44.2",
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"use_cache": true,
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"vocab_size": 128256
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}
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eval_results.json
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{
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"epoch": 0
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"eval_logits/chosen": 0.
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"eval_logits/rejected": 0.
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"eval_logps/chosen": -
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"eval_logps/rejected": -
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"eval_loss": 0.
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"eval_rewards/accuracies": 0.
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"eval_rewards/chosen":
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"eval_rewards/margins":
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"eval_rewards/rejected": -
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"eval_runtime":
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"eval_samples": 2500,
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"eval_samples_per_second":
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"eval_steps_per_second": 1.
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}
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{
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"epoch": 3.0,
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"eval_logits/chosen": 0.3730663061141968,
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"eval_logits/rejected": 0.4475269019603729,
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"eval_logps/chosen": -338.3392028808594,
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"eval_logps/rejected": -370.232666015625,
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"eval_loss": 0.6289177536964417,
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"eval_rewards/accuracies": 0.7405063509941101,
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"eval_rewards/chosen": 0.7478683590888977,
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"eval_rewards/margins": 4.585729122161865,
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"eval_rewards/rejected": -3.8378612995147705,
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"eval_runtime": 70.1775,
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"eval_samples": 2500,
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"eval_samples_per_second": 35.624,
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"eval_steps_per_second": 1.126
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}
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runs/Sep29_22-34-07_action-graph-trainer/events.out.tfevents.1727656053.action-graph-trainer.718565.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:71c573641baaf0e3920cfaf4291e3c5827addd7c33a74c2c3a9e9e8b40a32325
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size 828
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