---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-large-mnli-fer-finetuned
  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-large-mnli-fer-finetuned

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6940
- Accuracy: 0.5005

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7049        | 1.0   | 554  | 0.6895          | 0.5750   |
| 0.6981        | 2.0   | 1108 | 0.7054          | 0.5005   |
| 0.7039        | 3.0   | 1662 | 0.6936          | 0.5005   |
| 0.6976        | 4.0   | 2216 | 0.6935          | 0.4995   |
| 0.6991        | 5.0   | 2770 | 0.6940          | 0.5005   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1