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--- |
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library_name: transformers |
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base_model: data/OpenELM-1_1B-SFT |
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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: OpenELM-1_1B-DPO-2 |
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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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# OpenELM-1_1B-DPO-2 |
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This model is a fine-tuned version of [data/OpenELM-1_1B-SFT](https://huggingface.co/data/OpenELM-1_1B-SFT) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7793 |
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- Rewards/chosen: -11.75 |
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- Rewards/rejected: -13.6875 |
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- Rewards/accuracies: 0.7227 |
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- Rewards/margins: 1.9141 |
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- Logps/rejected: -564.0 |
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- Logps/chosen: -556.0 |
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- Logits/rejected: -13.0625 |
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- Logits/chosen: -13.3125 |
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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-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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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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- total_train_batch_size: 32 |
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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: 2 |
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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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| 0.6791 | 1.0 | 1911 | 0.7098 | -10.8125 | -11.9375 | 0.6992 | 1.1328 | -528.0 | -536.0 | -12.5625 | -12.6875 | |
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| 0.0506 | 2.0 | 3822 | 0.7793 | -11.75 | -13.6875 | 0.7227 | 1.9141 | -564.0 | -556.0 | -13.0625 | -13.3125 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.3.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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