---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: silviacamplani/distilbert-uncase-direct-finetuning-ai-ner
  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-uncase-direct-finetuning-ai-ner

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.6021
- Validation Loss: 1.6163
- 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': 2e-05, 'decay_steps': 60, '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 | Epoch |
|:----------:|:---------------:|:-----:|
| 3.2752     | 3.0320          | 0     |
| 2.7791     | 2.5293          | 1     |
| 2.2674     | 2.0340          | 2     |
| 1.8952     | 1.8222          | 3     |
| 1.7933     | 1.7669          | 4     |
| 1.7352     | 1.7158          | 5     |
| 1.6868     | 1.6706          | 6     |
| 1.6242     | 1.6412          | 7     |
| 1.5899     | 1.6234          | 8     |
| 1.6021     | 1.6163          | 9     |


### Framework versions

- Transformers 4.20.1
- TensorFlow 2.6.4
- Datasets 2.1.0
- Tokenizers 0.12.1