121c6f2962
Model: W-61/llama-3-8b-base-epsilon-dpo-hh-harmless-4xh200-batch-64-20260418-003215 Source: Original Platform
91 lines
5.7 KiB
Markdown
91 lines
5.7 KiB
Markdown
---
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library_name: transformers
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base_model: llama-3-8b-base-sft-hh-harmless-4xh200-batch-64
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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-harmless-4xh200-batch-64-20260418-003215
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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-harmless-4xh200-batch-64-20260418-003215
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This model is a fine-tuned version of [llama-3-8b-base-sft-hh-harmless-4xh200-batch-64](https://huggingface.co/llama-3-8b-base-sft-hh-harmless-4xh200-batch-64) on the Anthropic/hh-rlhf dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5778
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- Epsilon Dpo/beta: 0.0075
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- Epsilon Dpo/loss Margin Mean: 44.6202
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- Epsilon Dpo/beta Margin Mean: 0.3297
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- Epsilon Dpo/beta Margin Std: 0.5411
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- Epsilon Dpo/beta Margin Grad Mean: -0.4237
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- Epsilon Dpo/beta Margin Grad Std: 0.1239
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- Rewards/chosen: -0.6980
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- Rewards/rejected: -1.0277
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- Rewards/accuracies: 0.7192
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- Rewards/margins: 0.3297
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- Logps/chosen: -168.1115
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- Logps/rejected: -217.4212
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- Logps/ref Chosen: -74.8595
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- Logps/ref Rejected: -79.5490
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- Logits/chosen: 0.0396
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- Logits/rejected: -0.0641
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- Kl/p Epsilon Steps: 0.7196
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- Kl/n Epsilon Steps: 0.2799
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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: 8
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 64
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- total_eval_batch_size: 32
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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 | Epsilon Dpo/beta | Epsilon Dpo/loss Margin Mean | Epsilon Dpo/beta Margin Mean | Epsilon Dpo/beta Margin Std | Epsilon Dpo/beta Margin Grad Mean | Epsilon Dpo/beta Margin Grad Std | 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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| 1.3305 | 0.1512 | 100 | 0.6591 | 0.0821 | 1.4524 | 0.1163 | 0.4195 | -0.4725 | 0.0969 | -0.4073 | -0.5236 | 0.6298 | 0.1163 | -79.8024 | -85.9443 | -74.8595 | -79.5490 | -0.2133 | -0.2955 | 0.6109 | 0.3882 |
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| 0.9619 | 0.3023 | 200 | 0.5464 | 0.0537 | 12.5090 | 0.6642 | 1.1185 | -0.3726 | 0.2095 | -1.0244 | -1.6886 | 0.7183 | 0.6642 | -93.8833 | -111.0817 | -74.8595 | -79.5490 | -0.1899 | -0.3034 | 0.7240 | 0.2751 |
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| 1.0235 | 0.4535 | 300 | 0.5323 | 0.0324 | 22.9568 | 0.7358 | 1.1722 | -0.3618 | 0.2142 | -1.6265 | -2.3623 | 0.7284 | 0.7358 | -124.9662 | -152.6126 | -74.8595 | -79.5490 | -0.0481 | -0.1742 | 0.7293 | 0.2698 |
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| 1.132 | 0.6047 | 400 | 0.5402 | 0.0198 | 30.5708 | 0.5994 | 0.9731 | -0.3799 | 0.1895 | -1.2023 | -1.8017 | 0.7302 | 0.5994 | -135.4181 | -170.6785 | -74.8595 | -79.5490 | -0.0432 | -0.1614 | 0.7293 | 0.2698 |
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| 1.0834 | 0.7559 | 500 | 0.5507 | 0.0121 | 40.9401 | 0.4894 | 0.7940 | -0.3952 | 0.1670 | -1.0111 | -1.5005 | 0.7210 | 0.4894 | -158.3591 | -203.9887 | -74.8595 | -79.5490 | 0.0215 | -0.0872 | 0.7227 | 0.2764 |
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| 1.1666 | 0.9070 | 600 | 0.5778 | 0.0075 | 44.6202 | 0.3297 | 0.5411 | -0.4237 | 0.1239 | -0.6980 | -1.0277 | 0.7192 | 0.3297 | -168.1115 | -217.4212 | -74.8595 | -79.5490 | 0.0396 | -0.0641 | 0.7196 | 0.2799 |
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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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