---
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