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--- |
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library_name: transformers |
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license: gemma |
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base_model: google/gemma-2-9b-it |
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tags: |
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- llama-factory |
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- full |
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- trl |
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- dpo |
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- llama-factory |
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- generated_from_trainer |
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model-index: |
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- name: model |
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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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# model |
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This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on the cdc0b2d9-493b-4cb1-87e8-8fb1e3f4b247 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.9434 |
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- Rewards/chosen: -46.0543 |
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- Rewards/rejected: -47.7041 |
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- Rewards/accuracies: 0.6473 |
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- Rewards/margins: 1.6497 |
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- Logps/rejected: -4.7704 |
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- Logps/chosen: -4.6054 |
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- Logits/rejected: 14.6796 |
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- Logits/chosen: 14.4459 |
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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: 8e-07 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 32 |
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- gradient_accumulation_steps: 2 |
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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: 1.0 |
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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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| 3.9873 | 1.0 | 7344 | 3.9434 | -46.0543 | -47.7041 | 0.6473 | 1.6497 | -4.7704 | -4.6054 | 14.6796 | 14.4459 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.3.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.20.2 |
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