---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-Self-disclosure-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-Self-disclosure-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: 0.0525
- Accuracy: 0.9820
- Precision: 0.7838
- Recall: 0.8286
- F1: 0.8056

## 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: 1.5021066734744005e-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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3227        | 1.0   | 109  | 0.0632          | 0.9551   | 0.0       | 0.0    | 0.0    |
| 0.1297        | 2.0   | 218  | 0.0649          | 0.9782   | 0.7045    | 0.8857 | 0.7848 |
| 0.1211        | 3.0   | 327  | 0.0409          | 0.9692   | 0.6       | 0.9429 | 0.7333 |
| 0.1021        | 4.0   | 436  | 0.0599          | 0.9730   | 0.64      | 0.9143 | 0.7529 |
| 0.0797        | 5.0   | 545  | 0.0907          | 0.9756   | 0.66      | 0.9429 | 0.7765 |
| 0.0746        | 6.0   | 654  | 0.1045          | 0.9730   | 0.6346    | 0.9429 | 0.7586 |
| 0.0607        | 7.0   | 763  | 0.0720          | 0.9820   | 0.7333    | 0.9429 | 0.825  |
| 0.0419        | 8.0   | 872  | 0.0771          | 0.9782   | 0.7045    | 0.8857 | 0.7848 |
| 0.0632        | 9.0   | 981  | 0.0536          | 0.9846   | 0.7949    | 0.8857 | 0.8378 |
| 0.0456        | 10.0  | 1090 | 0.0525          | 0.9820   | 0.7838    | 0.8286 | 0.8056 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0