76 lines
2.6 KiB
Markdown
76 lines
2.6 KiB
Markdown
---
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library_name: transformers
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base_model: W-61/llama-3-8b-base-sft-ultrachat-8xh200
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tags:
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- alignment-handbook
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- beta-dpo
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- generated_from_trainer
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datasets:
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- HuggingFaceH4/ultrafeedback_binarized
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model-index:
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- name: llama-3-8b-base-beta-dpo-ultrafeedback-8xh200-20260410-201956
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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-beta-dpo-ultrafeedback-8xh200-20260410-201956
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This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-ultrachat-8xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-ultrachat-8xh200) on the HuggingFaceH4/ultrafeedback_binarized dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7668
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- Beta Dpo/gap Mean: 15.9231
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- Beta Dpo/gap Std: 25.9660
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- Beta Dpo/beta Used Raw: 0.0986
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- Beta Dpo/beta Used: 0.1434
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- Beta Dpo/mask Keep Frac: 1.0
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- Logits/chosen: -0.8035
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- Logits/rejected: -0.7974
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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: 8
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 128
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- total_eval_batch_size: 64
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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 | Beta Dpo/gap Mean | Beta Dpo/gap Std | Beta Dpo/beta Used Raw | Beta Dpo/beta Used | Beta Dpo/mask Keep Frac | Logits/chosen | Logits/rejected |
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|:-------------:|:------:|:----:|:---------------:|:-----------------:|:----------------:|:----------------------:|:------------------:|:-----------------------:|:-------------:|:---------------:|
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| 1.1971 | 0.4188 | 200 | 0.6549 | 11.0198 | 18.6390 | 0.0997 | 0.1243 | 1.0 | -0.7570 | -0.7553 |
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| 1.2165 | 0.8377 | 400 | 0.7668 | 15.9231 | 25.9660 | 0.0986 | 0.1434 | 1.0 | -0.8035 | -0.7974 |
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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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