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# distilbert-base-multilingual-cased-misogyny-sexism-decay0.01-fr-outofdomain

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: 3.1385
- Accuracy: 0.2369
- F1: 0.1919
- Precision: 0.1087
- Recall: 0.8148
- Mae: 0.7631
- Tn: 1279
- Fp: 6491
- Fn: 180
- Tp: 792

## 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    | Tn   | Fp   | Fn  | Tp  |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:----:|:----:|:---:|:---:|
| 0.2166        | 1.0   | 2233  | 1.2875          | 0.3377   | 0.2025 | 0.1169    | 0.7562 | 0.6623 | 2217 | 5553 | 237 | 735 |
| 0.2068        | 2.0   | 4466  | 1.8399          | 0.3141   | 0.2154 | 0.1234    | 0.8467 | 0.6859 | 1923 | 5847 | 149 | 823 |
| 0.2015        | 3.0   | 6699  | 1.5430          | 0.3543   | 0.2053 | 0.1189    | 0.75   | 0.6457 | 2368 | 5402 | 243 | 729 |
| 0.1739        | 4.0   | 8932  | 1.8406          | 0.2815   | 0.1911 | 0.1092    | 0.7634 | 0.7185 | 1719 | 6051 | 230 | 742 |
| 0.163         | 5.0   | 11165 | 2.0274          | 0.2170   | 0.1957 | 0.1105    | 0.8570 | 0.7830 | 1064 | 6706 | 139 | 833 |
| 0.1481        | 6.0   | 13398 | 1.6407          | 0.2467   | 0.1931 | 0.1096    | 0.8107 | 0.7533 | 1369 | 6401 | 184 | 788 |
| 0.1334        | 7.0   | 15631 | 3.0800          | 0.1875   | 0.1953 | 0.1097    | 0.8868 | 0.8125 | 777  | 6993 | 110 | 862 |
| 0.12          | 8.0   | 17864 | 2.5311          | 0.2183   | 0.1962 | 0.1108    | 0.8580 | 0.7817 | 1074 | 6696 | 138 | 834 |
| 0.1104        | 9.0   | 20097 | 2.9522          | 0.2135   | 0.1935 | 0.1092    | 0.8488 | 0.7865 | 1041 | 6729 | 147 | 825 |
| 0.0938        | 10.0  | 22330 | 3.1385          | 0.2369   | 0.1919 | 0.1087    | 0.8148 | 0.7631 | 1279 | 6491 | 180 | 792 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "distilbert-base-multilingual-cased-misogyny-sexism-decay0.01-fr-outofdomain", "results": []}]}
transformers pytorch distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilbert-base-multilingual-cased-misogyny-sexism-decay0.01-fr-outofdomain
===========================================================================


This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 3.1385
* Accuracy: 0.2369
* F1: 0.1919
* Precision: 0.1087
* Recall: 0.8148
* Mae: 0.7631
* Tn: 1279
* Fp: 6491
* Fn: 180
* Tp: 792


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



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1



### 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 ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1