81 lines
3.4 KiB
Markdown
81 lines
3.4 KiB
Markdown
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---
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library_name: transformers
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base_model: W-61/llama-3-8b-base-sft-hh-harmless-4xh200
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tags:
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- alignment-handbook
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- margin-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-margin-dpo-hh-harmless
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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-margin-dpo-hh-harmless
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This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-hh-harmless-4xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-hh-harmless-4xh200) on the Anthropic/hh-rlhf dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5259
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- Margin Dpo/margin Mean: 9.3649
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- Margin Dpo/margin Std: 14.8097
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- Logps/chosen: -92.0386
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- Logps/rejected: -106.0930
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- Logps/ref Chosen: -74.8595
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- Logps/ref Rejected: -79.5490
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- Logits/chosen: 0.3798
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- Logits/rejected: 0.3285
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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 | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
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|:-------------:|:------:|:----:|:---------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|
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| 1.3342 | 0.1512 | 100 | 0.6557 | 1.4205 | 4.9786 | -79.7014 | -85.8115 | -74.8595 | -79.5490 | 0.2556 | 0.2183 |
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| 0.9165 | 0.3023 | 200 | 0.5447 | 7.4721 | 12.5600 | -86.5507 | -98.7123 | -74.8595 | -79.5490 | 0.3345 | 0.2868 |
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| 0.9692 | 0.4535 | 300 | 0.5345 | 9.3794 | 14.9738 | -93.1794 | -107.2484 | -74.8595 | -79.5490 | 0.4017 | 0.3507 |
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| 1.084 | 0.6047 | 400 | 0.5337 | 8.8635 | 14.3566 | -91.2627 | -104.8157 | -74.8595 | -79.5490 | 0.3912 | 0.3394 |
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| 1.0037 | 0.7559 | 500 | 0.5277 | 9.5078 | 15.0672 | -92.1725 | -106.3698 | -74.8595 | -79.5490 | 0.3937 | 0.3419 |
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| 1.0459 | 0.9070 | 600 | 0.5259 | 9.3649 | 14.8097 | -92.0386 | -106.0930 | -74.8595 | -79.5490 | 0.3798 | 0.3285 |
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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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