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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: distilbertbaseuncasedz |
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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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# distilbertbaseuncasedz |
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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: 0.5368 |
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- Train End Logits Accuracy: 0.8401 |
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- Train Start Logits Accuracy: 0.8078 |
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- Validation Loss: 1.2427 |
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- Validation End Logits Accuracy: 0.7050 |
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- Validation Start Logits Accuracy: 0.6725 |
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- Epoch: 3 |
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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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 29508, '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 End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch | |
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|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:| |
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| 1.3338 | 0.6448 | 0.6045 | 1.1322 | 0.6906 | 0.6563 | 0 | |
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| 0.9044 | 0.7466 | 0.7090 | 1.0996 | 0.7032 | 0.6720 | 1 | |
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| 0.6756 | 0.8042 | 0.7680 | 1.1416 | 0.7047 | 0.6718 | 2 | |
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| 0.5368 | 0.8401 | 0.8078 | 1.2427 | 0.7050 | 0.6725 | 3 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- TensorFlow 2.6.4 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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