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--- |
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library_name: transformers |
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license: llama3.1 |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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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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- tanliboy/orca_dpo_pairs |
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model-index: |
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- name: lambda-llama-3-8b-dpo-test-orca |
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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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# lambda-llama-3-8b-dpo-test-orca |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the HuggingFaceH4/ultrafeedback_binarized and the tanliboy/orca_dpo_pairs datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4795 |
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- Rewards/chosen: -1.6860 |
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- Rewards/rejected: -2.8132 |
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- Rewards/accuracies: 0.7259 |
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- Rewards/margins: 1.1272 |
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- Logps/rejected: -645.5051 |
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- Logps/chosen: -549.3651 |
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- Logits/rejected: -2.6630 |
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- Logits/chosen: -2.5985 |
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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: 2e-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: 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: 32 |
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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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| 0.6011 | 0.1744 | 100 | 0.5738 | -0.8770 | -1.2808 | 0.6988 | 0.4038 | -492.2603 | -468.4565 | -2.4544 | -2.4042 | |
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| 0.5447 | 0.3489 | 200 | 0.5242 | -1.3236 | -2.0879 | 0.7289 | 0.7644 | -572.9752 | -513.1177 | -2.6319 | -2.5732 | |
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| 0.5173 | 0.5233 | 300 | 0.5003 | -1.6828 | -2.6810 | 0.7259 | 0.9982 | -632.2809 | -549.0404 | -2.6140 | -2.5556 | |
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| 0.5144 | 0.6978 | 400 | 0.4851 | -1.7107 | -2.8135 | 0.7319 | 1.1028 | -645.5279 | -551.8306 | -2.7027 | -2.6365 | |
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| 0.5162 | 0.8722 | 500 | 0.4798 | -1.7085 | -2.8440 | 0.7259 | 1.1355 | -648.5815 | -551.6072 | -2.6442 | -2.5812 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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