---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-large-1-second
  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-1-second

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: 0.9356
- Accuracy: 0.7715

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7871        | 1.0   | 769  | 1.6188          | 0.6694   |
| 1.5364        | 2.0   | 1538 | 1.4230          | 0.6828   |
| 1.4249        | 3.0   | 2307 | 1.3059          | 0.7067   |
| 1.336         | 4.0   | 3076 | 1.1884          | 0.7290   |
| 1.2366        | 5.0   | 3845 | 1.1214          | 0.74     |
| 1.1394        | 6.0   | 4614 | 1.0214          | 0.7601   |
| 1.0744        | 7.0   | 5383 | 0.9801          | 0.7664   |
| 1.0196        | 8.0   | 6152 | 0.9696          | 0.7646   |
| 0.9896        | 9.0   | 6921 | 0.9356          | 0.7715   |
| 0.9754        | 10.0  | 7690 | 0.9357          | 0.7704   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0