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--- |
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license: apache-2.0 |
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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_bert_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_bert_1 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.2128 |
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- Train Mae: 0.2623 |
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- Train Mse: 0.1098 |
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- Train Accuracy: 0.8615 |
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- Train R2-score: 0.8081 |
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- Validation Loss: 0.1657 |
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- Validation Mae: 0.3472 |
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- Validation Mse: 0.1644 |
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- Validation Accuracy: 0.7027 |
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- Validation R2-score: 0.8599 |
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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': 1e-04, '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 Accuracy | Train R2-score | Validation Loss | Validation Mae | Validation Mse | Validation Accuracy | Validation R2-score | Epoch | |
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|:----------:|:---------:|:---------:|:--------------:|:--------------:|:---------------:|:--------------:|:--------------:|:-------------------:|:-------------------:|:-----:| |
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| 0.6256 | 0.3353 | 0.1579 | 0.7615 | 0.4024 | 0.2916 | 0.4907 | 0.2909 | 0.3243 | 0.7810 | 0 | |
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| 0.3639 | 0.3290 | 0.1605 | 0.7077 | 0.3874 | 0.3009 | 0.5004 | 0.3003 | 0.3243 | 0.7733 | 1 | |
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| 0.1835 | 0.2940 | 0.1415 | 0.6615 | 0.7274 | 0.2086 | 0.3992 | 0.2075 | 0.3243 | 0.8417 | 2 | |
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| 0.1707 | 0.2955 | 0.1462 | 0.5846 | 0.7594 | 0.1872 | 0.3705 | 0.1859 | 0.3243 | 0.8547 | 3 | |
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| 0.1628 | 0.2740 | 0.1251 | 0.8077 | 0.7588 | 0.1867 | 0.3707 | 0.1854 | 0.4595 | 0.8547 | 4 | |
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| 0.1541 | 0.2695 | 0.1221 | 0.7769 | 0.7405 | 0.1851 | 0.3696 | 0.1839 | 0.5946 | 0.8549 | 5 | |
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| 0.2239 | 0.2983 | 0.1388 | 0.7154 | 0.7428 | 0.2561 | 0.4564 | 0.2552 | 0.3243 | 0.7987 | 6 | |
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| 0.1998 | 0.2815 | 0.1295 | 0.7538 | 0.7537 | 0.1979 | 0.3872 | 0.1968 | 0.3514 | 0.8473 | 7 | |
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| 0.1682 | 0.2743 | 0.1260 | 0.7692 | 0.7532 | 0.1515 | 0.3350 | 0.1500 | 0.9730 | 0.8691 | 8 | |
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| 0.2128 | 0.2623 | 0.1098 | 0.8615 | 0.8081 | 0.1657 | 0.3472 | 0.1644 | 0.7027 | 0.8599 | 9 | |
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### Framework versions |
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- Transformers 4.27.3 |
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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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