---
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_keras_callback
model-index:
- name: svenbl80/xlnet-base-cased-finetuned-mnli
  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/xlnet-base-cased-finetuned-mnli

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0221
- Validation Loss: 0.7391
- Train Accuracy: 0.8677
- 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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.4828     | 0.4066          | 0.8426         | 0     |
| 0.3364     | 0.3842          | 0.8598         | 1     |
| 0.2419     | 0.3913          | 0.8672         | 2     |
| 0.1713     | 0.4653          | 0.8624         | 3     |
| 0.1212     | 0.5090          | 0.8625         | 4     |
| 0.0857     | 0.5733          | 0.8684         | 5     |
| 0.0620     | 0.6176          | 0.8635         | 6     |
| 0.0435     | 0.6781          | 0.8670         | 7     |
| 0.0309     | 0.7102          | 0.8668         | 8     |
| 0.0221     | 0.7391          | 0.8677         | 9     |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.9.1
- Datasets 2.15.0
- Tokenizers 0.15.0