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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: luiscunhacsc/masked-lm-tpu |
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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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# luiscunhacsc/masked-lm-tpu |
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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: 9.8209 |
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- Train Accuracy: 0.0113 |
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- Validation Loss: 9.6999 |
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- Validation Accuracy: 0.0188 |
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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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0001, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 22325, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1175, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
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|:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
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| 10.2855 | 0.0000 | 10.2842 | 0.0 | 0 | |
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| 10.2729 | 0.0000 | 10.2651 | 0.0000 | 1 | |
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| 10.2599 | 0.0 | 10.2357 | 0.0000 | 2 | |
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| 10.2335 | 0.0 | 10.1943 | 0.0000 | 3 | |
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| 10.1915 | 0.0000 | 10.1447 | 0.0000 | 4 | |
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| 10.1449 | 0.0000 | 10.0705 | 0.0000 | 5 | |
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| 10.0750 | 0.0000 | 9.9926 | 0.0001 | 6 | |
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| 10.0099 | 0.0002 | 9.9074 | 0.0023 | 7 | |
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| 9.9197 | 0.0025 | 9.7964 | 0.0146 | 8 | |
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| 9.8209 | 0.0113 | 9.6999 | 0.0188 | 9 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- TensorFlow 2.12.0 |
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- Tokenizers 0.13.3 |
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