---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: tf-tpu/roberta-base-epochs-100
  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. -->

# tf-tpu/roberta-base-epochs-100

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: 1.6327
- Train Accuracy: 0.1001
- Validation Loss: 1.5273
- Validation Accuracy: 0.1035
- Epoch: 24

## 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0001, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 55765, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 2935, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001}
- training_precision: mixed_bfloat16

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 7.2121     | 0.0274         | 5.7188          | 0.0346              | 0     |
| 5.4335     | 0.0414         | 5.2266          | 0.0439              | 1     |
| 5.1579     | 0.0445         | 5.0625          | 0.0441              | 2     |
| 5.0231     | 0.0447         | 4.9453          | 0.0446              | 3     |
| 4.9323     | 0.0448         | 4.8633          | 0.0443              | 4     |
| 4.8672     | 0.0449         | 4.8789          | 0.0440              | 5     |
| 4.8200     | 0.0449         | 4.8164          | 0.0441              | 6     |
| 4.7841     | 0.0449         | 4.7734          | 0.0450              | 7     |
| 4.7546     | 0.0449         | 4.7539          | 0.0441              | 8     |
| 4.7288     | 0.0449         | 4.7305          | 0.0447              | 9     |
| 4.7084     | 0.0449         | 4.7422          | 0.0443              | 10    |
| 4.6884     | 0.0450         | 4.7148          | 0.0437              | 11    |
| 4.6764     | 0.0449         | 4.7070          | 0.0441              | 12    |
| 4.6637     | 0.0449         | 4.7227          | 0.0435              | 13    |
| 4.5963     | 0.0449         | 4.5195          | 0.0444              | 14    |
| 4.3462     | 0.0468         | 4.0742          | 0.0515              | 15    |
| 3.4139     | 0.0650         | 2.6348          | 0.0797              | 16    |
| 2.5336     | 0.0817         | 2.1816          | 0.0888              | 17    |
| 2.1859     | 0.0888         | 1.9648          | 0.0930              | 18    |
| 2.0043     | 0.0925         | 1.8154          | 0.0961              | 19    |
| 1.8887     | 0.0948         | 1.7129          | 0.0993              | 20    |
| 1.8058     | 0.0965         | 1.6729          | 0.0996              | 21    |
| 1.7402     | 0.0979         | 1.6191          | 0.1010              | 22    |
| 1.6861     | 0.0990         | 1.5693          | 0.1024              | 23    |
| 1.6327     | 0.1001         | 1.5273          | 0.1035              | 24    |


### Framework versions

- Transformers 4.27.0.dev0
- TensorFlow 2.9.1
- Tokenizers 0.13.2