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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: DLL888/deberta-v3-base-squad |
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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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# DLL888/deberta-v3-base-squad |
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the [SQuAD](https://huggingface.co/datasets/squad) dataset. |
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It achieves the following results on the evaluation set: |
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- Exact Match: 88.08893093661305 |
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- F1: 93.75543944888847 |
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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 Machine |
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Trained in Google Colab Pro with the following specs: |
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- A100-SXM4-40GB |
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- NVIDIA-SMI 460.32.03 |
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- Driver Version: 460.32.03 |
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- CUDA Version: 11.2 |
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Training took about 26 minutes for two epochs. |
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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': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 10538, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 500, 'power': 1.0, '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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| 1.0540 | 0.7261 | 0.6885 | 0.7617 | 0.7841 | 0.7530 | 0 | |
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| 0.6248 | 0.8212 | 0.7777 | 0.7594 | 0.7873 | 0.7569 | 1 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- TensorFlow 2.9.2 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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