---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base_brkfst_trainer
  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_brkfst_trainer

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: 0.0782
- Accuracy: 0.98

## 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: 32
- eval_batch_size: 32
- seed: 27
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6559        | 0.71  | 10   | 0.6907          | 0.8      |
| 0.5465        | 1.43  | 20   | 0.3822          | 0.84     |
| 0.4035        | 2.14  | 30   | 0.3178          | 0.93     |
| 0.3651        | 2.86  | 40   | 0.1117          | 0.94     |
| 0.1986        | 3.57  | 50   | 0.1832          | 0.95     |
| 0.2985        | 4.29  | 60   | 0.1133          | 0.96     |
| 0.141         | 5.0   | 70   | 0.1594          | 0.97     |
| 0.1334        | 5.71  | 80   | 0.2771          | 0.96     |
| 0.1874        | 6.43  | 90   | 0.0757          | 0.95     |
| 0.0594        | 7.14  | 100  | 0.2082          | 0.95     |
| 0.2883        | 7.86  | 110  | 0.2366          | 0.96     |
| 0.0459        | 8.57  | 120  | 0.1599          | 0.96     |
| 0.0733        | 9.29  | 130  | 0.2568          | 0.96     |
| 0.0483        | 10.0  | 140  | 0.3639          | 0.94     |
| 0.0487        | 10.71 | 150  | 0.2121          | 0.97     |
| 0.0339        | 11.43 | 160  | 0.1368          | 0.98     |
| 0.0463        | 12.14 | 170  | 0.1465          | 0.98     |
| 0.0025        | 12.86 | 180  | 0.2487          | 0.96     |
| 0.0009        | 13.57 | 190  | 0.0968          | 0.98     |
| 0.0003        | 14.29 | 200  | 0.0710          | 0.98     |
| 0.0003        | 15.0  | 210  | 0.0782          | 0.98     |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2