---
license: mit
tags:
- generated_from_trainer
model-index:
- name: roberta-base-mnli_MULTI
  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_MULTI

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: 0.6448
- Acc: 0.8397

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.4594        | 0.33  | 2000  | 0.4535          | 0.8292 |
| 0.4231        | 0.67  | 4000  | 0.4440          | 0.8323 |
| 0.4128        | 1.0   | 6000  | 0.4484          | 0.8352 |
| 0.3137        | 1.33  | 8000  | 0.4905          | 0.8338 |
| 0.3168        | 1.66  | 10000 | 0.4740          | 0.8372 |
| 0.3176        | 2.0   | 12000 | 0.4624          | 0.8415 |
| 0.2347        | 2.33  | 14000 | 0.5300          | 0.8361 |
| 0.2361        | 2.66  | 16000 | 0.5097          | 0.8378 |
| 0.238         | 3.0   | 18000 | 0.5016          | 0.8407 |
| 0.18          | 3.33  | 20000 | 0.5873          | 0.8382 |
| 0.179         | 3.66  | 22000 | 0.5917          | 0.8374 |
| 0.1786        | 4.0   | 24000 | 0.5868          | 0.8398 |
| 0.1409        | 4.33  | 26000 | 0.6468          | 0.8371 |
| 0.1395        | 4.66  | 28000 | 0.6423          | 0.8371 |
| 0.1401        | 4.99  | 30000 | 0.6448          | 0.8397 |


### Framework versions

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