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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-ipo-test |
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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-ipo-test |
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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: 0.8931 |
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- Rewards/chosen: -0.3610 |
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- Rewards/rejected: -0.5883 |
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- Rewards/accuracies: 0.7922 |
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- Rewards/margins: 0.2272 |
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- Logps/rejected: -3.1373 |
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- Logps/chosen: -2.5334 |
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- Logits/rejected: -2.9939 |
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- Logits/chosen: -2.9244 |
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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: 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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| 1.1749 | 0.1744 | 100 | 1.0763 | -0.1732 | -0.3120 | 0.7892 | 0.1388 | -2.4465 | -2.0638 | -2.5676 | -2.5133 | |
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| 0.9802 | 0.3489 | 200 | 0.9501 | -0.3184 | -0.5302 | 0.8012 | 0.2118 | -2.9922 | -2.4269 | -2.7873 | -2.7230 | |
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| 0.9548 | 0.5233 | 300 | 0.9136 | -0.3761 | -0.6028 | 0.8163 | 0.2267 | -3.1736 | -2.5710 | -2.8788 | -2.8087 | |
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| 0.9834 | 0.6978 | 400 | 0.9041 | -0.3384 | -0.5537 | 0.8042 | 0.2153 | -3.0509 | -2.4770 | -2.9371 | -2.8667 | |
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| 0.9967 | 0.8722 | 500 | 0.8938 | -0.3750 | -0.6076 | 0.7892 | 0.2326 | -3.1855 | -2.5684 | -3.0293 | -2.9592 | |
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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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