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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: nandysoham16/11-clustered_aug |
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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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# nandysoham16/11-clustered_aug |
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This model is a fine-tuned version of [Rocketknight1/distilbert-base-uncased-finetuned-squad](https://huggingface.co/Rocketknight1/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: 0.6603 |
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- Train End Logits Accuracy: 0.8121 |
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- Train Start Logits Accuracy: 0.7740 |
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- Validation Loss: 0.8493 |
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- Validation End Logits Accuracy: 0.7641 |
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- Validation Start Logits Accuracy: 0.7206 |
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- Epoch: 1 |
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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': 928, '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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| 1.0062 | 0.7301 | 0.6882 | 0.8708 | 0.7571 | 0.7147 | 0 | |
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| 0.6603 | 0.8121 | 0.7740 | 0.8493 | 0.7641 | 0.7206 | 1 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- TensorFlow 2.9.2 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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