---
license: mit
base_model: ayshi/basic_roberta
tags:
- generated_from_keras_callback
model-index:
- name: ayshi/basic_roberta
  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. -->

# ayshi/basic_roberta

This model is a fine-tuned version of [ayshi/basic_roberta](https://huggingface.co/ayshi/basic_roberta) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0085
- Validation Loss: 1.0970
- Train Accuracy: 0.8267
- Epoch: 20

## 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': 960, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.1061     | 0.9567          | 0.7778         | 0     |
| 0.0565     | 1.0825          | 0.7778         | 1     |
| 0.0362     | 1.0696          | 0.7822         | 2     |
| 0.0396     | 1.0904          | 0.7956         | 3     |
| 0.0308     | 1.0044          | 0.8044         | 4     |
| 0.0748     | 1.0578          | 0.8133         | 5     |
| 0.0392     | 0.9964          | 0.8222         | 6     |
| 0.0166     | 1.0293          | 0.8089         | 7     |
| 0.0174     | 0.9895          | 0.8178         | 8     |
| 0.0114     | 1.0403          | 0.8267         | 9     |
| 0.0141     | 1.0086          | 0.8178         | 10    |
| 0.0145     | 1.0403          | 0.8089         | 11    |
| 0.0194     | 1.3127          | 0.7822         | 12    |
| 0.0134     | 1.2929          | 0.7911         | 13    |
| 0.0377     | 0.8565          | 0.8133         | 14    |
| 0.0251     | 0.9806          | 0.8222         | 15    |
| 0.0130     | 1.0757          | 0.8356         | 16    |
| 0.0100     | 1.1304          | 0.8            | 17    |
| 0.0103     | 1.0859          | 0.8133         | 18    |
| 0.0078     | 1.1050          | 0.8311         | 19    |
| 0.0085     | 1.0970          | 0.8267         | 20    |


### Framework versions

- Transformers 4.34.0
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.14.1