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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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- accuracy |
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- spearmanr |
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- pearsonr |
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model-index: |
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- name: estimation-prometheus-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-prometheus-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: 2.4192 |
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- Accuracy: 0.4235 |
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- Spearmanr: 0.4236 |
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- Kendalltau: 0.3285 |
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- Pearsonr: 0.4779 |
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- Rmse: 1.0679 |
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- Mae: 0.8129 |
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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: 16 |
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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: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Spearmanr | Kendalltau | Pearsonr | Rmse | Mae | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:----------:|:--------:|:------:|:------:| |
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| 4.38 | 0.2094 | 500 | 4.5787 | 0.3141 | 0.0241 | 0.0177 | 0.0263 | 1.3354 | 1.0377 | |
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| 3.4137 | 0.4188 | 1000 | 3.0643 | 0.3410 | 0.1413 | 0.1072 | 0.1555 | 1.2135 | 0.9624 | |
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| 2.8427 | 0.6281 | 1500 | 2.7700 | 0.3728 | 0.2953 | 0.2259 | 0.3155 | 1.1565 | 0.8857 | |
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| 2.7978 | 0.8375 | 2000 | 2.6360 | 0.3887 | 0.3524 | 0.2708 | 0.3844 | 1.1258 | 0.8747 | |
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| 2.5765 | 1.0469 | 2500 | 2.5750 | 0.4095 | 0.3797 | 0.2938 | 0.4191 | 1.1107 | 0.8387 | |
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| 2.5941 | 1.2563 | 3000 | 2.5392 | 0.4175 | 0.3839 | 0.2963 | 0.4286 | 1.1012 | 0.8465 | |
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| 2.3148 | 1.4657 | 3500 | 2.4901 | 0.4105 | 0.4069 | 0.3154 | 0.4536 | 1.0851 | 0.8245 | |
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| 2.6814 | 1.6750 | 4000 | 2.4642 | 0.4135 | 0.4100 | 0.3173 | 0.4635 | 1.0794 | 0.8221 | |
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| 2.5861 | 1.8844 | 4500 | 2.4569 | 0.4115 | 0.4152 | 0.3213 | 0.4668 | 1.0782 | 0.8185 | |
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| 2.5241 | 2.0938 | 5000 | 2.4320 | 0.4115 | 0.4196 | 0.3263 | 0.4733 | 1.0712 | 0.8132 | |
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| 2.5838 | 2.3032 | 5500 | 2.4252 | 0.4185 | 0.4197 | 0.3260 | 0.4755 | 1.0693 | 0.8125 | |
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| 2.4464 | 2.5126 | 6000 | 2.4232 | 0.4185 | 0.4217 | 0.3270 | 0.4768 | 1.0695 | 0.8110 | |
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| 2.4398 | 2.7219 | 6500 | 2.4218 | 0.4185 | 0.4221 | 0.3276 | 0.4764 | 1.0686 | 0.8122 | |
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| 2.3042 | 2.9313 | 7000 | 2.4192 | 0.4235 | 0.4236 | 0.3285 | 0.4779 | 1.0679 | 0.8129 | |
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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 |
