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---
license: apache-2.0
tags:
- generated_from_keras_callback
base_model: silviacamplani/distilbert-finetuned-dapt_tapt-lm-ai
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
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