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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: mallikrao2/qa-finetuned-swag |
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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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# mallikrao2/qa-finetuned-swag |
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This model is a fine-tuned version of [mallikrao2/sQuad_bertmodel1_](https://huggingface.co/mallikrao2/sQuad_bertmodel1_) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0020 |
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- Train Accuracy: 0.9994 |
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- Validation Loss: 1.9750 |
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- Validation Accuracy: 0.7508 |
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- Epoch: 19 |
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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': 5e-05, 'decay_steps': 66860, '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 Accuracy | Validation Loss | Validation Accuracy | Epoch | |
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|:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
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| 0.8405 | 0.6630 | 0.6156 | 0.7596 | 0 | |
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| 0.4697 | 0.8233 | 0.6102 | 0.7643 | 1 | |
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| 0.2479 | 0.9087 | 0.7102 | 0.7573 | 2 | |
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| 0.1571 | 0.9439 | 0.8434 | 0.7482 | 3 | |
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| 0.1139 | 0.9599 | 1.0923 | 0.7453 | 4 | |
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| 0.0881 | 0.9698 | 1.0614 | 0.7421 | 5 | |
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| 0.0705 | 0.9758 | 1.1311 | 0.7412 | 6 | |
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| 0.0577 | 0.9802 | 1.1761 | 0.7387 | 7 | |
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| 0.0453 | 0.9845 | 1.3310 | 0.7446 | 8 | |
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| 0.0379 | 0.9869 | 1.3076 | 0.7361 | 9 | |
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| 0.0301 | 0.9898 | 1.3147 | 0.7434 | 10 | |
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| 0.0228 | 0.9923 | 1.6641 | 0.7388 | 11 | |
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| 0.0195 | 0.9932 | 1.6168 | 0.7397 | 12 | |
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| 0.0165 | 0.9948 | 1.6042 | 0.7458 | 13 | |
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| 0.0118 | 0.9960 | 1.6922 | 0.7426 | 14 | |
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| 0.0098 | 0.9970 | 1.7052 | 0.7449 | 15 | |
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| 0.0059 | 0.9982 | 1.8137 | 0.7453 | 16 | |
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| 0.0040 | 0.9986 | 1.9369 | 0.7504 | 17 | |
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| 0.0032 | 0.9991 | 1.9089 | 0.7498 | 18 | |
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| 0.0020 | 0.9994 | 1.9750 | 0.7508 | 19 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- TensorFlow 2.8.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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