---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: svenbl80/roberta-base-finetuned-new-mnli-run-1
  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. -->

# svenbl80/roberta-base-finetuned-new-mnli-run-1

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: 0.0248
- Validation Loss: 0.7357
- Train Accuracy: 0.8661
- 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 245430, '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}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.4558     | 0.3972          | 0.8495         | 0     |
| 0.3309     | 0.3834          | 0.8520         | 1     |
| 0.2465     | 0.4150          | 0.8627         | 2     |
| 0.1784     | 0.4412          | 0.8670         | 3     |
| 0.1288     | 0.4816          | 0.8626         | 4     |
| 0.0926     | 0.5470          | 0.8647         | 5     |
| 0.0666     | 0.5634          | 0.8669         | 6     |
| 0.0477     | 0.6574          | 0.8648         | 7     |
| 0.0345     | 0.6919          | 0.8641         | 8     |
| 0.0248     | 0.7357          | 0.8661         | 9     |


### Framework versions

- Transformers 4.28.0
- TensorFlow 2.9.1
- Datasets 2.15.0
- Tokenizers 0.13.3