81 lines
2.2 KiB
Markdown
81 lines
2.2 KiB
Markdown
---
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library_name: transformers
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license: llama3.1
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base_model: meta-llama/Llama-3.1-8B
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tags:
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- alignment-handbook
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- trl
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- dpo
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- generated_from_trainer
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- trl
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- 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: zephyr-8b-dpo-full
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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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# zephyr-8b-dpo-full
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This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) on the HuggingFaceH4/ultrafeedback_binarized dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5372
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- Rewards/chosen: -1.1911
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- Rewards/rejected: -2.0021
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- Rewards/accuracies: 0.7656
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- Rewards/margins: 0.8110
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- Logps/rejected: -481.7125
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- Logps/chosen: -401.6271
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- Logits/rejected: -0.5622
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- Logits/chosen: -0.5978
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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: 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: 4
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- total_train_batch_size: 128
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- total_eval_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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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/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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| 0.5134 | 0.9984 | 477 | 0.5372 | -1.1911 | -2.0021 | 0.7656 | 0.8110 | -481.7125 | -401.6271 | -0.5622 | -0.5978 |
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### Framework versions
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- Transformers 4.45.2
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- Pytorch 2.5.1+rocm6.2
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- Datasets 3.2.0
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- Tokenizers 0.20.3
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