---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_keras_callback
model-index:
- name: betteib/mlm-tn-v2-7ep
  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. -->

# betteib/mlm-tn-v2-7ep

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 8.1140
- Train Accuracy: 0.0049
- Validation Loss: 8.1063
- Validation Accuracy: 0.0046
- Epoch: 6

## 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': 118, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 6, '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: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 8.1066     | 0.0049         | 8.1434          | 0.0044              | 0     |
| 8.1105     | 0.0048         | 8.1242          | 0.0045              | 1     |
| 8.1123     | 0.0048         | 8.1227          | 0.0045              | 2     |
| 8.1128     | 0.0049         | 8.0994          | 0.0048              | 3     |
| 8.1190     | 0.0048         | 8.1180          | 0.0046              | 4     |
| 8.1079     | 0.0049         | 8.1067          | 0.0046              | 5     |
| 8.1140     | 0.0049         | 8.1063          | 0.0046              | 6     |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.19.1
- Tokenizers 0.13.3