---
license: mit
base_model: roberta-base
tags:
- generated_from_keras_callback
model-index:
- name: Drigoro/my_awesome_model3
  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. -->

# Drigoro/my_awesome_model3

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.5285
- Validation Loss: 1.5080
- Train Accuracy: 0.5554
- 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: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1220, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 1.4494     | 1.3028          | 0.5110         | 0     |
| 1.2173     | 1.2547          | 0.5350         | 1     |
| 1.0579     | 1.2659          | 0.5595         | 2     |
| 0.9320     | 1.2806          | 0.5503         | 3     |
| 0.8199     | 1.3338          | 0.5375         | 4     |
| 0.7389     | 1.3642          | 0.5457         | 5     |
| 0.6608     | 1.4301          | 0.5477         | 6     |
| 0.6115     | 1.4599          | 0.5544         | 7     |
| 0.5594     | 1.4930          | 0.5503         | 8     |
| 0.5285     | 1.5080          | 0.5554         | 9     |


### Framework versions

- Transformers 4.40.2
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1