81 lines
3.2 KiB
Markdown
81 lines
3.2 KiB
Markdown
---
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library_name: transformers
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base_model: W-61/llama-3-8b-base-sft-hh-helpful-8xh200
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tags:
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- alignment-handbook
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- epsilon-dpo
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- generated_from_trainer
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datasets:
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- Anthropic/hh-rlhf
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model-index:
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- name: llama-3-8b-base-epsilon-dpo-hh-helpful-8xh200-20260410-233108
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# llama-3-8b-base-epsilon-dpo-hh-helpful-8xh200-20260410-233108
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This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-hh-helpful-8xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-hh-helpful-8xh200) on the Anthropic/hh-rlhf dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6443
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- Rewards/chosen: -0.4430
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- Rewards/rejected: -0.5884
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- Rewards/accuracies: 0.6402
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- Rewards/margins: 0.1454
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- Logps/chosen: -208.1799
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- Logps/rejected: -243.5746
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- Logps/ref Chosen: -87.8236
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- Logps/ref Rejected: -82.8189
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- Logits/chosen: -0.8325
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- Logits/rejected: -0.7259
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- Kl/p Epsilon Steps: 0.6150
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- Kl/n Epsilon Steps: 0.3850
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-07
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- total_train_batch_size: 128
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- total_eval_batch_size: 128
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected | Kl/p Epsilon Steps | Kl/n Epsilon Steps |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|:------------------:|:------------------:|
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| 0.6236 | 0.2941 | 100 | 0.6636 | -0.3033 | -0.3895 | 0.6124 | 0.0862 | -127.6472 | -134.3018 | -87.8236 | -82.8189 | -1.2261 | -1.1807 | 0.5760 | 0.4236 |
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| 0.5934 | 0.5882 | 200 | 0.6429 | -0.5156 | -0.6820 | 0.6324 | 0.1663 | -182.9084 | -209.3034 | -87.8236 | -82.8189 | -0.9817 | -0.8951 | 0.6037 | 0.3958 |
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| 0.6156 | 0.8824 | 300 | 0.6443 | -0.4430 | -0.5884 | 0.6402 | 0.1454 | -208.1799 | -243.5746 | -87.8236 | -82.8189 | -0.8325 | -0.7259 | 0.6150 | 0.3850 |
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### Framework versions
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- Transformers 4.51.0
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.21.4
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