---
license: mit
base_model: roberta-large
tags:
- generated_from_keras_callback
model-index:
- name: svenbl80/roberta-large-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/roberta-large-finetuned-mnli

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0360
- Validation Loss: 0.5873
- Train Accuracy: 0.8758
- Epoch: 17

## 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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 736290, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.4137     | 0.3492          | 0.8715         | 0     |
| 0.3226     | 0.3720          | 0.8733         | 1     |
| 0.2768     | 0.4048          | 0.8728         | 2     |
| 0.2267     | 0.3649          | 0.8808         | 3     |
| 0.1890     | 0.4397          | 0.8646         | 4     |
| 0.1621     | 0.4422          | 0.8772         | 5     |
| 0.1378     | 0.4529          | 0.8758         | 6     |
| 0.1191     | 0.4992          | 0.8642         | 7     |
| 0.1102     | 0.4681          | 0.8693         | 8     |
| 0.0970     | 0.4758          | 0.8779         | 9     |
| 0.0851     | 0.4850          | 0.8630         | 10    |
| 0.0884     | 0.5140          | 0.8767         | 11    |
| 0.0644     | 0.5284          | 0.8801         | 12    |
| 0.0605     | 0.5239          | 0.8765         | 13    |
| 0.0554     | 0.7088          | 0.8433         | 14    |
| 0.0460     | 0.5774          | 0.8722         | 15    |
| 0.0386     | 0.5296          | 0.8741         | 16    |
| 0.0360     | 0.5873          | 0.8758         | 17    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.11.0
- Datasets 2.15.0
- Tokenizers 0.15.0