---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: FacebookAI_roberta-large_custom_data
  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. -->

# FacebookAI_roberta-large_custom_data

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: 0.3779
- Precision Macro: 0.8141
- Recall Macro: 0.8170
- F1 Macro: 0.8155
- Accuracy: 0.8117

## 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: 16
- seed: 42
- 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision Macro | Recall Macro | F1 Macro | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------:|:--------:|
| 0.5113        | 1.0   | 270  | 0.3779          | 0.8141          | 0.8170       | 0.8155   | 0.8117   |
| 0.3962        | 2.0   | 540  | 0.4214          | 0.8266          | 0.8093       | 0.8125   | 0.8200   |
| 0.2556        | 3.0   | 810  | 0.4619          | 0.8149          | 0.8106       | 0.8112   | 0.8135   |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0