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---
tags:
- generated_from_keras_callback
model-index:
- name: silviacamplani/distilbert-finetuned-dapt_tapt-ner-ai
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-ai
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.8595
- Validation Loss: 0.8604
- Train Precision: 0.3378
- Train Recall: 0.3833
- Train F1: 0.3591
- Train Accuracy: 0.7860
- 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': 350, '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 |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 2.5333 | 1.7392 | 0.0 | 0.0 | 0.0 | 0.6480 | 0 |
| 1.5890 | 1.4135 | 0.0 | 0.0 | 0.0 | 0.6480 | 1 |
| 1.3635 | 1.2627 | 0.0 | 0.0 | 0.0 | 0.6483 | 2 |
| 1.2366 | 1.1526 | 0.1538 | 0.0920 | 0.1151 | 0.6921 | 3 |
| 1.1296 | 1.0519 | 0.2147 | 0.2147 | 0.2147 | 0.7321 | 4 |
| 1.0374 | 0.9753 | 0.2743 | 0.2981 | 0.2857 | 0.7621 | 5 |
| 0.9639 | 0.9202 | 0.3023 | 0.3373 | 0.3188 | 0.7693 | 6 |
| 0.9097 | 0.8829 | 0.3215 | 0.3714 | 0.3447 | 0.7795 | 7 |
| 0.8756 | 0.8635 | 0.3280 | 0.3850 | 0.3542 | 0.7841 | 8 |
| 0.8595 | 0.8604 | 0.3378 | 0.3833 | 0.3591 | 0.7860 | 9 |
### Framework versions
- Transformers 4.20.1
- TensorFlow 2.6.4
- Datasets 2.1.0
- Tokenizers 0.12.1
|