---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: roberta-base-pr
  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-pr

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1841
- F1 Macro: 0.6097
- Precision: 0.6135
- Recall: 0.6205
- Accuracy: 0.7627

## 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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | Precision | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| No log        | 1.0   | 240  | 2.3617          | 0.0348   | 0.1449    | 0.1032 | 0.0749   |
| No log        | 2.0   | 480  | 0.8375          | 0.5802   | 0.5865    | 0.6081 | 0.7399   |
| 1.9571        | 3.0   | 720  | 0.8221          | 0.5996   | 0.6040    | 0.6244 | 0.7471   |
| 1.9571        | 4.0   | 960  | 0.8073          | 0.6168   | 0.6096    | 0.6356 | 0.7617   |
| 0.9292        | 5.0   | 1200 | 0.7768          | 0.6273   | 0.6273    | 0.6369 | 0.7742   |
| 0.9292        | 6.0   | 1440 | 0.9650          | 0.6009   | 0.6025    | 0.6211 | 0.7445   |
| 0.5053        | 7.0   | 1680 | 1.0663          | 0.6072   | 0.6218    | 0.6186 | 0.7622   |
| 0.5053        | 8.0   | 1920 | 1.1841          | 0.6097   | 0.6135    | 0.6205 | 0.7627   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1