---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: v9_checkpoints
  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. -->

# v9_checkpoints

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6931
- Accuracy: 0.4851

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6962        | 1.0   | 746  | 0.6931          | 0.5478   |
| 0.6971        | 2.0   | 1492 | 0.6931          | 0.5350   |
| 0.6958        | 3.0   | 2238 | 0.6931          | 0.5538   |
| 0.6951        | 4.0   | 2984 | 0.6931          | 0.5595   |
| 0.6953        | 5.0   | 3730 | 0.6931          | 0.5360   |
| 0.6959        | 6.0   | 4476 | 0.6931          | 0.4509   |
| 0.6957        | 7.0   | 5222 | 0.6931          | 0.5357   |
| 0.6939        | 8.0   | 5968 | 0.6931          | 0.5273   |
| 0.6946        | 9.0   | 6714 | 0.6931          | 0.4495   |
| 0.6941        | 10.0  | 7460 | 0.6931          | 0.4851   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1