---
base_model: NLP-LTU/bertweet-large-sexism-detector
tags:
- generated_from_trainer
model-index:
- name: bertweet-large-sexism-detector
  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. -->

# bertweet-large-sexism-detector

This model is a fine-tuned version of [NLP-LTU/bertweet-large-sexism-detector](https://huggingface.co/NLP-LTU/bertweet-large-sexism-detector) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9648
- Icm: 0.2479
- Icmnorm: 0.6258
- Fmeasure: 0.7526

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Icm     | Icmnorm | Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:--------:|
| 0.8774        | 1.0   | 771  | 1.1253          | -0.1346 | 0.4317  | 0.5634   |
| 0.9551        | 2.0   | 1542 | 0.8275          | 0.1264  | 0.5641  | 0.7110   |
| 0.9559        | 3.0   | 2313 | 0.9648          | 0.2479  | 0.6258  | 0.7526   |
| 0.6926        | 4.0   | 3084 | 1.5632          | 0.1570  | 0.5797  | 0.7172   |
| 0.4547        | 5.0   | 3855 | 1.8028          | 0.1284  | 0.5652  | 0.7098   |
| 0.2611        | 6.0   | 4626 | 1.9528          | 0.2025  | 0.6027  | 0.7359   |
| 0.1528        | 7.0   | 5397 | 2.1400          | 0.1119  | 0.5568  | 0.7073   |
| 0.1173        | 8.0   | 6168 | 2.1909          | 0.1524  | 0.5773  | 0.7195   |
| 0.1096        | 9.0   | 6939 | 2.4630          | 0.1166  | 0.5591  | 0.7073   |
| 0.0535        | 10.0  | 7710 | 2.4917          | 0.1809  | 0.5918  | 0.7276   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2