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--- |
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license: mit |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Regression_roberta_1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# Regression_roberta_1 |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.3891 |
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- Train Mae: 0.3117 |
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- Train Mse: 0.1477 |
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- Train R2-score: 0.7113 |
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- Train Accuracy: 0.7077 |
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- Validation Loss: 0.3272 |
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- Validation Mae: 0.3256 |
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- Validation Mse: 0.1253 |
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- Validation R2-score: 0.8839 |
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- Validation Accuracy: 0.9459 |
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- Epoch: 9 |
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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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- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 2e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train Mae | Train Mse | Train R2-score | Train Accuracy | Validation Loss | Validation Mae | Validation Mse | Validation R2-score | Validation Accuracy | Epoch | |
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|:----------:|:---------:|:---------:|:--------------:|:--------------:|:---------------:|:--------------:|:--------------:|:-------------------:|:-------------------:|:-----:| |
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| 0.4486 | 0.2939 | 0.1319 | 0.7250 | 0.7769 | 0.4177 | 0.4165 | 0.2221 | 0.8321 | 0.3243 | 0 | |
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| 0.3684 | 0.2898 | 0.1342 | 0.5541 | 0.7462 | 0.4019 | 0.4006 | 0.2091 | 0.8409 | 0.3243 | 1 | |
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| 0.3423 | 0.2854 | 0.1299 | 0.7355 | 0.7462 | 0.3971 | 0.3958 | 0.2050 | 0.8438 | 0.3243 | 2 | |
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| 0.3514 | 0.2890 | 0.1324 | 0.7935 | 0.7538 | 0.3552 | 0.3538 | 0.1640 | 0.8681 | 0.9459 | 3 | |
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| 0.3722 | 0.3107 | 0.1525 | 0.5604 | 0.7000 | 0.3448 | 0.3432 | 0.1484 | 0.8750 | 0.9459 | 4 | |
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| 0.3996 | 0.2949 | 0.1305 | 0.7869 | 0.8231 | 0.3692 | 0.3677 | 0.1794 | 0.8514 | 0.4865 | 5 | |
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| 0.3441 | 0.2895 | 0.1322 | 0.7546 | 0.7538 | 0.3186 | 0.3169 | 0.1159 | 0.8860 | 0.9459 | 6 | |
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| 0.3898 | 0.2921 | 0.1255 | 0.5919 | 0.7692 | 0.4107 | 0.4095 | 0.2160 | 0.8366 | 0.3243 | 7 | |
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| 0.3552 | 0.2868 | 0.1297 | 0.7113 | 0.7538 | 0.4426 | 0.4415 | 0.2434 | 0.8179 | 0.3243 | 8 | |
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| 0.3891 | 0.3117 | 0.1477 | 0.7113 | 0.7077 | 0.3272 | 0.3256 | 0.1253 | 0.8839 | 0.9459 | 9 | |
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### Framework versions |
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- Transformers 4.27.2 |
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- TensorFlow 2.11.0 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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