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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: Trickshotblaster/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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# Trickshotblaster/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: 5.0588 |
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- Train Accuracy: 0.0445 |
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- Validation Loss: 5.0495 |
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- Validation Accuracy: 0.0449 |
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- Epoch: 29 |
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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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| 5.1057 | 0.0447 | 5.1128 | 0.0445 | 0 | |
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| 5.1366 | 0.0445 | 5.1449 | 0.0446 | 1 | |
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| 5.1152 | 0.0445 | 5.1034 | 0.0441 | 2 | |
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| 5.1297 | 0.0442 | 5.0708 | 0.0449 | 3 | |
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| 5.1002 | 0.0448 | 5.0494 | 0.0449 | 4 | |
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| 5.1155 | 0.0443 | 5.1304 | 0.0440 | 5 | |
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| 5.0949 | 0.0445 | 5.1050 | 0.0441 | 6 | |
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| 5.0747 | 0.0451 | 5.0769 | 0.0446 | 7 | |
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| 5.0840 | 0.0447 | 5.0664 | 0.0442 | 8 | |
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| 5.0828 | 0.0446 | 5.1446 | 0.0438 | 9 | |
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| 5.0994 | 0.0444 | 5.0545 | 0.0454 | 10 | |
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| 5.1009 | 0.0448 | 5.0466 | 0.0452 | 11 | |
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| 5.1028 | 0.0442 | 5.0538 | 0.0458 | 12 | |
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| 5.0771 | 0.0447 | 5.0645 | 0.0445 | 13 | |
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| 5.0809 | 0.0443 | 5.0884 | 0.0438 | 14 | |
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| 5.0831 | 0.0445 | 5.0946 | 0.0450 | 15 | |
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| 5.0753 | 0.0444 | 5.1057 | 0.0441 | 16 | |
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| 5.0786 | 0.0447 | 5.1212 | 0.0439 | 17 | |
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| 5.0674 | 0.0446 | 5.0428 | 0.0453 | 18 | |
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| 5.0737 | 0.0447 | 5.0155 | 0.0458 | 19 | |
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| 5.0510 | 0.0448 | 5.1046 | 0.0443 | 20 | |
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| 5.0815 | 0.0446 | 5.0959 | 0.0441 | 21 | |
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| 5.0518 | 0.0450 | 5.0441 | 0.0453 | 22 | |
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| 5.0514 | 0.0449 | 5.0835 | 0.0442 | 23 | |
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| 5.0400 | 0.0449 | 5.0802 | 0.0444 | 24 | |
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| 5.0708 | 0.0446 | 5.0587 | 0.0440 | 25 | |
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| 5.0745 | 0.0441 | 5.0809 | 0.0440 | 26 | |
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| 5.0467 | 0.0446 | 5.0542 | 0.0444 | 27 | |
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| 5.0190 | 0.0449 | 5.0191 | 0.0453 | 28 | |
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| 5.0588 | 0.0445 | 5.0495 | 0.0449 | 29 | |
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### Framework versions |
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- Transformers 4.30.1 |
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- TensorFlow 2.12.0 |
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- Tokenizers 0.13.3 |
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