---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: svenbl80/roberta-base-finetuned-new-mnli-run-4
  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-4

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: 0.0254
- Validation Loss: 0.7597
- Train Accuracy: 0.8592
- 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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.4543     | 0.3920          | 0.8526         | 0     |
| 0.3298     | 0.3979          | 0.8546         | 1     |
| 0.2478     | 0.4089          | 0.8603         | 2     |
| 0.1821     | 0.4577          | 0.8575         | 3     |
| 0.1309     | 0.4901          | 0.8556         | 4     |
| 0.0947     | 0.5514          | 0.8551         | 5     |
| 0.0682     | 0.6368          | 0.8553         | 6     |
| 0.0489     | 0.6589          | 0.8577         | 7     |
| 0.0343     | 0.7216          | 0.8599         | 8     |
| 0.0254     | 0.7597          | 0.8592         | 9     |


### Framework versions

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