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--- |
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license: apache-2.0 |
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base_model: distilbert-base-cased-distilled-squad |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: badokorach/distilbert-base-cased-distilled-agric-431223 |
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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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# badokorach/distilbert-base-cased-distilled-agric-431223 |
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This model is a fine-tuned version of [distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert-base-cased-distilled-squad) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.2983 |
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- Validation Loss: 0.0 |
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- Epoch: 18 |
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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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 1020, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.02} |
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- training_precision: mixed_float16 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 2.7789 | 0.0 | 0 | |
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| 1.9616 | 0.0 | 1 | |
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| 1.7173 | 0.0 | 2 | |
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| 1.4140 | 0.0 | 3 | |
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| 1.2717 | 0.0 | 4 | |
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| 1.1056 | 0.0 | 5 | |
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| 0.9403 | 0.0 | 6 | |
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| 0.8326 | 0.0 | 7 | |
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| 0.7148 | 0.0 | 8 | |
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| 0.6565 | 0.0 | 9 | |
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| 0.5461 | 0.0 | 10 | |
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| 0.4961 | 0.0 | 11 | |
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| 0.4480 | 0.0 | 12 | |
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| 0.4153 | 0.0 | 13 | |
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| 0.3842 | 0.0 | 14 | |
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| 0.3511 | 0.0 | 15 | |
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| 0.3115 | 0.0 | 16 | |
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| 0.3033 | 0.0 | 17 | |
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| 0.2983 | 0.0 | 18 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.14.0 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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