79 lines
2.8 KiB
Markdown
79 lines
2.8 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-ultrachat-8xh200
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tags:
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- alignment-handbook
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- r-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-r-dpo-ultrafeedback-4xh200
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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-r-dpo-ultrafeedback-4xh200
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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: 0.5080
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- R Dpo/chosen Len: 291.2620
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- R Dpo/rejected Len: 248.3960
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- R Dpo/length Delta: 42.8660
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- R Dpo/regularization Term: 0.0
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- Logps/chosen: -288.0679
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- Logps/rejected: -272.9751
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- Logps/ref Chosen: -289.1346
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- Logps/ref Rejected: -264.7782
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- Logits/chosen: -0.7442
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- Logits/rejected: -0.7460
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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: 4
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- eval_batch_size: 4
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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: 8
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- total_train_batch_size: 128
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- total_eval_batch_size: 16
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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 | R Dpo/chosen Len | R Dpo/rejected Len | R Dpo/length Delta | R Dpo/regularization Term | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
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|:-------------:|:------:|:----:|:---------------:|:----------------:|:------------------:|:------------------:|:-------------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|
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| 4.178 | 0.4188 | 200 | 0.5266 | 291.2620 | 248.3960 | 42.8660 | 0.0 | -287.2393 | -271.3152 | -289.1346 | -264.7782 | -0.7479 | -0.7490 |
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| 4.0423 | 0.8377 | 400 | 0.5080 | 291.2620 | 248.3960 | 42.8660 | 0.0 | -288.0679 | -272.9751 | -289.1346 | -264.7782 | -0.7442 | -0.7460 |
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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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