readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: silviacamplani/distilbert-finetuned-dapt_tapt-ner-music
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # silviacamplani/distilbert-finetuned-dapt_tapt-ner-music
  
  This model is a fine-tuned version of [silviacamplani/distilbert-finetuned-dapt_tapt-lm-ai](https://huggingface.co/silviacamplani/distilbert-finetuned-dapt_tapt-lm-ai) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.6073
  - Validation Loss: 0.7078
  - Train Precision: 0.5337
  - Train Recall: 0.5986
  - Train F1: 0.5643
  - Train Accuracy: 0.8344
  - Epoch: 9
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - 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}
  - training_precision: mixed_float16
  
  ### Training results
  
  | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
  | 2.6231     | 2.0072          | 0.0             | 0.0          | 0.0      | 0.5482         | 0     |
  | 1.7195     | 1.5337          | 0.1905          | 0.0072       | 0.0139   | 0.5597         | 1     |
  | 1.3447     | 1.2423          | 0.3073          | 0.3510       | 0.3277   | 0.6910         | 2     |
  | 1.1065     | 1.0569          | 0.4162          | 0.4536       | 0.4341   | 0.7195         | 3     |
  | 0.9326     | 0.9225          | 0.5050          | 0.5473       | 0.5253   | 0.7689         | 4     |
  | 0.8061     | 0.8345          | 0.5306          | 0.5770       | 0.5528   | 0.8011         | 5     |
  | 0.7118     | 0.7749          | 0.5292          | 0.5878       | 0.5569   | 0.8176         | 6     |
  | 0.6636     | 0.7366          | 0.5314          | 0.5950       | 0.5614   | 0.8242         | 7     |
  | 0.6284     | 0.7158          | 0.5330          | 0.5968       | 0.5631   | 0.8321         | 8     |
  | 0.6073     | 0.7078          | 0.5337          | 0.5986       | 0.5643   | 0.8344         | 9     |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.6.4
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  