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---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: silviacamplani/distilbert-finetuned-dapt-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-ner-music
This model is a fine-tuned version of [silviacamplani/distilbert-finetuned-dapt-lm-ai](https://huggingface.co/silviacamplani/distilbert-finetuned-dapt-lm-ai) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.7656
- Validation Loss: 0.8288
- Train Precision: 0.5590
- Train Recall: 0.5968
- Train F1: 0.5773
- Train Accuracy: 0.7761
- Epoch: 6
## 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 |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 2.5668 | 1.9780 | 0.0 | 0.0 | 0.0 | 0.5482 | 0 |
| 1.7189 | 1.4888 | 0.1152 | 0.0396 | 0.0589 | 0.5905 | 1 |
| 1.3060 | 1.2236 | 0.3797 | 0.3564 | 0.3677 | 0.6839 | 2 |
| 1.0982 | 1.0637 | 0.4716 | 0.4635 | 0.4675 | 0.7155 | 3 |
| 0.9450 | 0.9504 | 0.5176 | 0.5167 | 0.5171 | 0.7385 | 4 |
| 0.8398 | 0.8775 | 0.5474 | 0.5671 | 0.5570 | 0.7579 | 5 |
| 0.7656 | 0.8288 | 0.5590 | 0.5968 | 0.5773 | 0.7761 | 6 |
### Framework versions
- Transformers 4.20.1
- TensorFlow 2.6.4
- Datasets 2.1.0
- Tokenizers 0.12.1
|