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--- |
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library_name: peft |
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license: gemma |
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base_model: google/gemma-2-2b-jpn-it |
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tags: |
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- generated_from_trainer |
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metrics: |
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- spearmanr |
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- pearsonr |
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model-index: |
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- name: estimation-reward-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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# estimation-reward-gemma-2-2b |
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This model is a fine-tuned version of [google/gemma-2-2b-jpn-it](https://huggingface.co/google/gemma-2-2b-jpn-it) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 93.8438 |
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- Spearmanr: 0.6688 |
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- Kendalltau: 0.4828 |
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- Pearsonr: 0.0 |
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- Rmse: 9.6873 |
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- Mae: 7.4340 |
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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: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine_with_min_lr |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 2.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Spearmanr | Kendalltau | Pearsonr | Rmse | Mae | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:----------:|:--------:|:-------:|:-------:| |
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| 142.0495 | 0.2094 | 500 | 172.4941 | 0.1755 | 0.1193 | 0.0 | 13.1337 | 10.1489 | |
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| 114.1114 | 0.4188 | 1000 | 145.3719 | 0.4083 | 0.2799 | 0.0 | 12.0570 | 9.3769 | |
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| 126.2303 | 0.6281 | 1500 | 123.7460 | 0.5220 | 0.3660 | 0.0 | 11.1241 | 8.5576 | |
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| 104.0802 | 0.8375 | 2000 | 110.0878 | 0.5964 | 0.4219 | 0.0 | 10.4923 | 8.0832 | |
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| 92.9514 | 1.0469 | 2500 | 101.4019 | 0.6340 | 0.4530 | 0.0 | 10.0698 | 7.7131 | |
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| 89.5989 | 1.2563 | 3000 | 98.1783 | 0.6485 | 0.4649 | 0.0 | 9.9085 | 7.6020 | |
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| 76.1914 | 1.4657 | 3500 | 96.0021 | 0.6582 | 0.4736 | 0.0 | 9.7981 | 7.5160 | |
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| 81.2849 | 1.6750 | 4000 | 95.4644 | 0.6645 | 0.4783 | 0.0 | 9.7706 | 7.5254 | |
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| 75.9316 | 1.8844 | 4500 | 93.8438 | 0.6688 | 0.4828 | 0.0 | 9.6873 | 7.4340 | |
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### Framework versions |
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- PEFT 0.15.1 |
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- Transformers 4.50.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
