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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: vrx2/distilbert-base-uncased-finetuned-squad |
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results: [] |
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datasets: |
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- squad_v2 |
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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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# vrx2/distilbert-base-uncased-finetuned-squad |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.9741 |
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- Train End Logits Accuracy: 0.7291 |
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- Train Start Logits Accuracy: 0.6924 |
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- Validation Loss: 1.1179 |
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- Validation End Logits Accuracy: 0.6960 |
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- Validation Start Logits Accuracy: 0.6616 |
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- Epoch: 1 |
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## Model description |
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just a bench test of my laptop's capabilities |
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## Intended uses & limitations |
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testing purposes |
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## Training and evaluation data |
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trained on squad v2 |
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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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 11064, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, '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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| 1.5188 | 0.6049 | 0.5697 | 1.1433 | 0.6878 | 0.6498 | 0 | |
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| 0.9741 | 0.7291 | 0.6924 | 1.1179 | 0.6960 | 0.6616 | 1 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- TensorFlow 2.14.0 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
