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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: silviacamplani/distilbert-finetuned-ner-music |
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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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# silviacamplani/distilbert-finetuned-ner-music |
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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: 0.6767 |
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- Validation Loss: 0.7802 |
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- Train Precision: 0.5256 |
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- Train Recall: 0.5824 |
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- Train F1: 0.5525 |
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- Train Accuracy: 0.8017 |
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- Epoch: 9 |
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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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 370, '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, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000} |
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- training_precision: mixed_float16 |
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### Training results |
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| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch | |
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|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:| |
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| 2.6671 | 2.0032 | 0.0 | 0.0 | 0.0 | 0.5482 | 0 | |
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| 1.7401 | 1.5194 | 0.1820 | 0.0693 | 0.1004 | 0.5902 | 1 | |
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| 1.3487 | 1.2627 | 0.2628 | 0.2952 | 0.2781 | 0.6766 | 2 | |
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| 1.1390 | 1.0990 | 0.4018 | 0.4527 | 0.4257 | 0.7181 | 3 | |
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| 0.9823 | 0.9837 | 0.4575 | 0.4887 | 0.4726 | 0.7311 | 4 | |
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| 0.8741 | 0.9022 | 0.5008 | 0.5338 | 0.5168 | 0.7544 | 5 | |
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| 0.7904 | 0.8449 | 0.5085 | 0.5626 | 0.5342 | 0.7776 | 6 | |
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| 0.7327 | 0.8097 | 0.5211 | 0.5779 | 0.5480 | 0.7917 | 7 | |
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| 0.7000 | 0.7872 | 0.5281 | 0.5842 | 0.5547 | 0.7975 | 8 | |
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| 0.6767 | 0.7802 | 0.5256 | 0.5824 | 0.5525 | 0.8017 | 9 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- TensorFlow 2.6.4 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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