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--- |
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license: gemma |
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base_model: google/gemma-2-2b |
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tags: |
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- easylm |
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- alignment-handbook |
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- trl |
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- sft |
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- generated_from_trainer |
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- trl |
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- sft |
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- generated_from_trainer |
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datasets: |
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- ultrafeedback-sft |
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model-index: |
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- name: easylm-ultrafeedback-sft-gemma-2-2b |
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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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# easylm-ultrafeedback-sft-gemma-2-2b |
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This model is a fine-tuned version of [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b) on the ultrafeedback-sft dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2897 |
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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: 3e-06 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 2 |
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- total_eval_batch_size: 2 |
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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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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 1.5578 | 0.0371 | 500 | 1.4651 | |
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| 1.4645 | 0.0742 | 1000 | 1.4362 | |
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| 1.4198 | 0.1113 | 1500 | 1.4196 | |
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| 1.3469 | 0.1484 | 2000 | 1.4051 | |
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| 1.3816 | 0.1855 | 2500 | 1.3920 | |
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| 1.3653 | 0.2226 | 3000 | 1.3809 | |
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| 1.4087 | 0.2596 | 3500 | 1.3715 | |
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| 1.2973 | 0.2967 | 4000 | 1.3615 | |
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| 1.348 | 0.3338 | 4500 | 1.3545 | |
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| 1.4639 | 0.3709 | 5000 | 1.3480 | |
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| 1.4405 | 0.4080 | 5500 | 1.3408 | |
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| 1.2926 | 0.4451 | 6000 | 1.3349 | |
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| 1.3452 | 0.4822 | 6500 | 1.3268 | |
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| 1.3076 | 0.5193 | 7000 | 1.3202 | |
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| 1.2696 | 0.5564 | 7500 | 1.3154 | |
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| 1.3833 | 0.5935 | 8000 | 1.3104 | |
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| 1.3217 | 0.6306 | 8500 | 1.3060 | |
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| 1.2351 | 0.6677 | 9000 | 1.3026 | |
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| 1.5295 | 0.7047 | 9500 | 1.2990 | |
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| 1.293 | 0.7418 | 10000 | 1.2967 | |
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| 1.2231 | 0.7789 | 10500 | 1.2942 | |
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| 1.2721 | 0.8160 | 11000 | 1.2926 | |
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| 1.3877 | 0.8531 | 11500 | 1.2913 | |
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| 1.2929 | 0.8902 | 12000 | 1.2903 | |
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| 1.4017 | 0.9273 | 12500 | 1.2900 | |
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| 1.2126 | 0.9644 | 13000 | 1.2897 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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