0 1
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-base-multilingual-cased-finetuned-misogyny-en-it
  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. -->

# distilbert-base-multilingual-cased-finetuned-misogyny-en-it

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0096
- Accuracy: 0.9985
- F1: 0.9984
- Precision: 0.9969
- Recall: 1.0
- Mae: 0.0015

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall | Mae    |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
| 0.3169        | 1.0   | 1006  | 0.3924          | 0.8154   | 0.8322 | 0.7388    | 0.9526 | 0.1846 |
| 0.2567        | 2.0   | 2012  | 0.3045          | 0.8700   | 0.8779 | 0.8       | 0.9726 | 0.1300 |
| 0.1829        | 3.0   | 3018  | 0.1385          | 0.9525   | 0.9524 | 0.9172    | 0.9905 | 0.0475 |
| 0.1465        | 4.0   | 4024  | 0.0465          | 0.9863   | 0.9858 | 0.9822    | 0.9895 | 0.0137 |
| 0.0683        | 5.0   | 5030  | 0.0290          | 0.9939   | 0.9937 | 0.9885    | 0.9989 | 0.0061 |
| 0.06          | 6.0   | 6036  | 0.0232          | 0.9949   | 0.9948 | 0.9916    | 0.9979 | 0.0051 |
| 0.0195        | 7.0   | 7042  | 0.0189          | 0.9965   | 0.9963 | 0.9927    | 1.0    | 0.0035 |
| 0.0172        | 8.0   | 8048  | 0.0105          | 0.9980   | 0.9979 | 0.9958    | 1.0    | 0.0020 |
| 0.0248        | 9.0   | 9054  | 0.0099          | 0.9980   | 0.9979 | 0.9958    | 1.0    | 0.0020 |
| 0.0058        | 10.0  | 10060 | 0.0096          | 0.9985   | 0.9984 | 0.9969    | 1.0    | 0.0015 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.9.0+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
