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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: nandysoham/Gregorian_calendar-theme-finetuned-overfinetuned |
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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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# nandysoham/Gregorian_calendar-theme-finetuned-overfinetuned |
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This model is a fine-tuned version of [nandysoham/distilbert-base-uncased-finetuned-squad](https://huggingface.co/nandysoham/distilbert-base-uncased-finetuned-squad) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.1838 |
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- Train End Logits Accuracy: 0.9500 |
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- Train Start Logits Accuracy: 0.9688 |
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- Validation Loss: 2.0017 |
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- Validation End Logits Accuracy: 0.5238 |
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- Validation Start Logits Accuracy: 0.4762 |
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- Epoch: 8 |
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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': 100, '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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| 2.2861 | 0.3688 | 0.4062 | 1.6038 | 0.5952 | 0.5714 | 0 | |
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| 1.2774 | 0.5938 | 0.5938 | 1.4240 | 0.5952 | 0.5714 | 1 | |
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| 0.8752 | 0.7000 | 0.7375 | 1.4402 | 0.5952 | 0.5476 | 2 | |
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| 0.5245 | 0.8250 | 0.8438 | 1.5027 | 0.6429 | 0.5952 | 3 | |
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| 0.4132 | 0.8313 | 0.8938 | 1.6252 | 0.5714 | 0.5 | 4 | |
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| 0.3140 | 0.9000 | 0.9062 | 1.7524 | 0.5476 | 0.4762 | 5 | |
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| 0.2534 | 0.9688 | 0.9312 | 1.8646 | 0.5238 | 0.4762 | 6 | |
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| 0.1999 | 0.9500 | 0.9563 | 1.9513 | 0.5238 | 0.4762 | 7 | |
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| 0.1838 | 0.9500 | 0.9688 | 2.0017 | 0.5238 | 0.4762 | 8 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- TensorFlow 2.9.2 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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