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--- |
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license: other |
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base_model: google/gemma-2b |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: gemma_2b_scotus |
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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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# gemma_2b_scotus |
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This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6088 |
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- Accuracy: 0.5186 |
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- F1 Macro: 0.3274 |
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- F1 Micro: 0.5186 |
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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-06 |
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- train_batch_size: 16 |
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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: 2 |
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- total_train_batch_size: 32 |
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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: linear |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:| |
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| 2.2227 | 0.32 | 50 | 2.1669 | 0.31 | 0.0991 | 0.31 | |
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| 1.7367 | 0.64 | 100 | 1.8375 | 0.425 | 0.2124 | 0.425 | |
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| 1.6836 | 0.96 | 150 | 1.6646 | 0.4836 | 0.2551 | 0.4836 | |
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| 1.1611 | 1.27 | 200 | 1.8198 | 0.4386 | 0.2719 | 0.4386 | |
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| 1.0922 | 1.59 | 250 | 1.7039 | 0.49 | 0.2888 | 0.49 | |
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| 1.0527 | 1.91 | 300 | 1.6088 | 0.5186 | 0.3274 | 0.5186 | |
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| 0.5763 | 2.23 | 350 | 1.7765 | 0.4929 | 0.3462 | 0.4929 | |
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| 0.4645 | 2.55 | 400 | 1.7984 | 0.4986 | 0.3434 | 0.4986 | |
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| 0.394 | 2.87 | 450 | 1.7742 | 0.4993 | 0.3472 | 0.4993 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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