---
license: mit
tags:
- generated_from_trainer
model-index:
- name: roberta-base-mnli_VALUE
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# roberta-base-mnli_VALUE

This model is a fine-tuned version of [WillHeld/roberta-base-mnli](https://huggingface.co/WillHeld/roberta-base-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5880
- Acc: 0.8680

## 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:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Acc    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.3487        | 0.33  | 2000  | 0.3948          | 0.8588 |
| 0.3008        | 0.65  | 4000  | 0.4038          | 0.8605 |
| 0.2767        | 0.98  | 6000  | 0.3889          | 0.8648 |
| 0.2186        | 1.3   | 8000  | 0.4352          | 0.8654 |
| 0.2177        | 1.63  | 10000 | 0.4251          | 0.8654 |
| 0.2212        | 1.96  | 12000 | 0.4155          | 0.8681 |
| 0.1638        | 2.28  | 14000 | 0.4783          | 0.8638 |
| 0.1592        | 2.61  | 16000 | 0.4572          | 0.8673 |
| 0.1565        | 2.93  | 18000 | 0.4669          | 0.8683 |
| 0.1213        | 3.26  | 20000 | 0.5114          | 0.8693 |
| 0.1154        | 3.59  | 22000 | 0.5604          | 0.8668 |
| 0.1159        | 3.91  | 24000 | 0.5143          | 0.8707 |
| 0.0952        | 4.24  | 26000 | 0.5900          | 0.8661 |
| 0.0881        | 4.56  | 28000 | 0.6000          | 0.8663 |
| 0.0879        | 4.89  | 30000 | 0.5880          | 0.8680 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.12.1