---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: roberta-large-csb
  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-csb

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2625
- Accuracy: 0.8857
- F1: 0.8860

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3718        | 1.0   | 228  | 0.2774          | 0.8747   | 0.8748 |
| 0.3126        | 2.0   | 456  | 0.2625          | 0.8857   | 0.8860 |
| 0.2053        | 3.0   | 684  | 0.3058          | 0.8791   | 0.8787 |
| 0.1797        | 4.0   | 912  | 0.4676          | 0.8615   | 0.8601 |
| 0.1087        | 5.0   | 1140 | 0.8824          | 0.8330   | 0.8288 |
| 0.0827        | 6.0   | 1368 | 0.9341          | 0.8637   | 0.8616 |
| 0.0336        | 7.0   | 1596 | 0.9355          | 0.8571   | 0.8552 |
| 0.0077        | 8.0   | 1824 | 0.9166          | 0.8725   | 0.8720 |
| 0.0011        | 9.0   | 2052 | 0.9783          | 0.8747   | 0.8740 |
| 0.0001        | 10.0  | 2280 | 1.0445          | 0.8703   | 0.8692 |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.2.1
- Datasets 4.4.1
- Tokenizers 0.22.1