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Training in progress epoch 0
Browse files- README.md +13 -14
- tf_model.h5 +1 -1
README.md
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-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.
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- Train Accuracy: 0.
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- Train F1 M: 0.
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- Train Precision M: 0.
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- Train Recall M:
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- Validation Loss: 0.
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- Validation Accuracy: 0.
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- Validation F1 M: 0.
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- Validation Precision M: 0.
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- Validation Recall M:
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- Epoch:
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps':
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- training_precision: float32
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### Training results
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| Train Loss | Train Accuracy | Train F1 M | Train Precision M | Train Recall M | Validation Loss | Validation Accuracy | Validation F1 M | Validation Precision M | Validation Recall M | Epoch |
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|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
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| 0.6835 | 0.5807 | 0.6227 | 0.4066 | 1.5628 | 0.6756 | 0.5937 | 0.6390 | 0.4063 | 1.7203 | 1 |
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### Framework versions
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 0.3898
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- Train Accuracy: 0.8294
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- Train F1 M: 0.3411
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- Train Precision M: 0.2894
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- Train Recall M: 0.4810
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- Validation Loss: 0.2440
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- Validation Accuracy: 0.8984
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- Validation F1 M: 0.5087
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- Validation Precision M: 0.3814
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- Validation Recall M: 0.8079
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- Epoch: 0
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3790, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
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- training_precision: float32
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### Training results
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| Train Loss | Train Accuracy | Train F1 M | Train Precision M | Train Recall M | Validation Loss | Validation Accuracy | Validation F1 M | Validation Precision M | Validation Recall M | Epoch |
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|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
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| 0.3898 | 0.8294 | 0.3411 | 0.2894 | 0.4810 | 0.2440 | 0.8984 | 0.5087 | 0.3814 | 0.8079 | 0 |
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### Framework versions
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tf_model.h5
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size 1341127728
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version https://git-lfs.github.com/spec/v1
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size 1341127728
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