---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-Suggestions-badareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current
  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-Suggestions-badareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current

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: 0.2123
- Accuracy: 0.9255
- Precision: 0.5882
- Recall: 0.5714
- F1: 0.5797

## 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: 2.878285533930529e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4106        | 1.0   | 173  | 0.5091          | 0.7933   | 0.2541    | 0.6714 | 0.3686 |
| 0.2807        | 2.0   | 346  | 0.0956          | 0.9114   | 0.6667    | 0.0286 | 0.0548 |
| 0.2358        | 3.0   | 519  | 0.0803          | 0.9101   | 0.0       | 0.0    | 0.0    |
| 0.1777        | 4.0   | 692  | 0.1143          | 0.9358   | 0.6613    | 0.5857 | 0.6212 |
| 0.1659        | 5.0   | 865  | 0.1055          | 0.9307   | 0.6       | 0.6857 | 0.64   |
| 0.2001        | 6.0   | 1038 | 0.1580          | 0.9332   | 0.65      | 0.5571 | 0.6    |
| 0.1621        | 7.0   | 1211 | 0.1430          | 0.9281   | 0.5854    | 0.6857 | 0.6316 |
| 0.1263        | 8.0   | 1384 | 0.1817          | 0.9320   | 0.6104    | 0.6714 | 0.6395 |
| 0.1101        | 9.0   | 1557 | 0.1930          | 0.9281   | 0.6061    | 0.5714 | 0.5882 |
| 0.1033        | 10.0  | 1730 | 0.2123          | 0.9255   | 0.5882    | 0.5714 | 0.5797 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0