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

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1086
- F1 Macro: 0.6212
- Precision: 0.6133
- Recall: 0.6330
- Accuracy: 0.7726

## 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  | 1.6547          | 0.4481   | 0.4726    | 0.5217 | 0.5525   |
| No log        | 2.0   | 480  | 0.7853          | 0.5905   | 0.6003    | 0.6054 | 0.7497   |
| 1.8301        | 3.0   | 720  | 0.8548          | 0.5993   | 0.6286    | 0.6309 | 0.7513   |
| 1.8301        | 4.0   | 960  | 0.7731          | 0.6257   | 0.6300    | 0.6352 | 0.7706   |
| 0.8772        | 5.0   | 1200 | 0.7724          | 0.6353   | 0.6364    | 0.6460 | 0.7846   |
| 0.8772        | 6.0   | 1440 | 0.8417          | 0.6325   | 0.6403    | 0.6354 | 0.7836   |
| 0.4566        | 7.0   | 1680 | 1.1086          | 0.6212   | 0.6133    | 0.6330 | 0.7726   |


### Framework versions

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