Training in progress epoch 0
Browse files
README.md
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This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss:
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- Validation Loss:
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- Train Accuracy: 0.
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- Train Precision: 0.
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- Train Recall: 0.
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- Train F1: 0.
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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', '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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate':
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- training_precision: float32
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### Training results
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| Train Loss | Validation Loss | Train Accuracy | Train Precision | Train Recall | Train F1 | Epoch |
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|:----------:|:---------------:|:--------------:|:---------------:|:------------:|:--------:|:-----:|
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| 1.
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| 0.8750 | 0.9204 | 0.5525 | 0.5123 | 0.5525 | 0.5003 | 1 |
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| 0.8071 | 0.9152 | 0.5567 | 0.5396 | 0.5567 | 0.5414 | 2 |
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| 0.7594 | 0.9245 | 0.5551 | 0.5581 | 0.5551 | 0.5553 | 3 |
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| 0.7224 | 0.9349 | 0.5550 | 0.5512 | 0.5550 | 0.5501 | 4 |
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| 0.6944 | 0.9348 | 0.5568 | 0.5590 | 0.5568 | 0.5578 | 5 |
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### Framework versions
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This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 1.2460
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- Validation Loss: 1.1773
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- Train Accuracy: 0.3708
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- Train Precision: 0.1375
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- Train Recall: 0.3708
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- Train F1: 0.2006
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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', '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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.02, 'decay_steps': 11870, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, '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 | Validation Loss | Train Accuracy | Train Precision | Train Recall | Train F1 | Epoch |
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|:----------:|:---------------:|:--------------:|:---------------:|:------------:|:--------:|:-----:|
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| 1.2460 | 1.1773 | 0.3708 | 0.1375 | 0.3708 | 0.2006 | 0 |
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### Framework versions
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logs/train/events.out.tfevents.1716096062.6264913a9602.740.7.v2
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logs/validation/events.out.tfevents.1716096098.6264913a9602.740.8.v2
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tf_model.h5
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