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--- |
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license: apache-2.0 |
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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: Regression_albert_NOaug_MSEloss |
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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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# Regression_albert_NOaug_MSEloss |
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4715 |
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- Mse: 0.4715 |
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- Mae: 0.6001 |
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- R2: 0.1320 |
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- Accuracy: 0.4737 |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:--------:| |
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| No log | 1.0 | 33 | 0.2966 | 0.2966 | 0.4630 | 0.1139 | 0.7568 | |
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| No log | 2.0 | 66 | 0.2679 | 0.2679 | 0.4039 | 0.1995 | 0.7568 | |
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| No log | 3.0 | 99 | 0.4088 | 0.4088 | 0.5125 | -0.2213 | 0.5405 | |
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| No log | 4.0 | 132 | 0.4331 | 0.4331 | 0.5399 | -0.2939 | 0.4865 | |
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| No log | 5.0 | 165 | 0.3699 | 0.3699 | 0.4317 | -0.1053 | 0.6757 | |
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| No log | 6.0 | 198 | 0.3456 | 0.3456 | 0.4117 | -0.0325 | 0.6216 | |
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| No log | 7.0 | 231 | 0.3371 | 0.3371 | 0.4155 | -0.0072 | 0.6757 | |
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| No log | 8.0 | 264 | 0.3261 | 0.3261 | 0.3811 | 0.0256 | 0.7297 | |
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| No log | 9.0 | 297 | 0.2312 | 0.2312 | 0.2705 | 0.3092 | 0.8108 | |
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| No log | 10.0 | 330 | 0.3194 | 0.3194 | 0.3681 | 0.0457 | 0.6757 | |
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| No log | 11.0 | 363 | 0.3638 | 0.3638 | 0.4124 | -0.0870 | 0.6757 | |
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| No log | 12.0 | 396 | 0.3101 | 0.3101 | 0.3630 | 0.0734 | 0.7027 | |
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| No log | 13.0 | 429 | 0.2762 | 0.2762 | 0.3221 | 0.1748 | 0.7568 | |
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| No log | 14.0 | 462 | 0.2970 | 0.2970 | 0.3376 | 0.1126 | 0.7297 | |
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| No log | 15.0 | 495 | 0.3185 | 0.3185 | 0.3532 | 0.0483 | 0.7297 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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