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# detect-femicide-news-xlmr

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0161
- Accuracy: 0.9973
- Precision Neg: 0.9975
- Precision Pos: 0.9967
- Recall Neg: 0.9988
- Recall Pos: 0.9933
- F1 Score Neg: 0.9981
- F1 Score Pos: 0.9950

## 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 1996
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Neg | Precision Pos | Recall Neg | Recall Pos | F1 Score Neg | F1 Score Pos |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:-------------:|:----------:|:----------:|:------------:|:------------:|
| 0.2758        | 1.0   | 204  | 0.1001          | 0.9718   | 0.9741        | 0.9654        | 0.9875     | 0.93       | 0.9808       | 0.9474       |
| 0.0782        | 2.0   | 408  | 0.0505          | 0.9809   | 0.9839        | 0.9729        | 0.99       | 0.9567     | 0.9869       | 0.9647       |
| 0.0501        | 3.0   | 612  | 0.0272          | 0.9927   | 0.9962        | 0.9834        | 0.9938     | 0.99       | 0.9950       | 0.9867       |
| 0.0389        | 4.0   | 816  | 0.0201          | 0.9945   | 0.9938        | 0.9966        | 0.9988     | 0.9833     | 0.9963       | 0.9899       |
| 0.031         | 5.0   | 1020 | 0.0175          | 0.9964   | 0.9963        | 0.9966        | 0.9988     | 0.99       | 0.9975       | 0.9933       |
| 0.0235        | 6.0   | 1224 | 0.0161          | 0.9973   | 0.9975        | 0.9967        | 0.9988     | 0.9933     | 0.9981       | 0.9950       |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.2+cu113
- Datasets 1.18.3
- Tokenizers 0.11.0

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "detect-femicide-news-xlmr", "results": []}]}
transformers pytorch tensorboard xlm-roberta text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

detect-femicide-news-xlmr
=========================


This model is a fine-tuned version of xlm-roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0161
* Accuracy: 0.9973
* Precision Neg: 0.9975
* Precision Pos: 0.9967
* Recall Neg: 0.9988
* Recall Pos: 0.9933
* F1 Score Neg: 0.9981
* F1 Score Pos: 0.9950


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: 1e-05
* train\_batch\_size: 128
* eval\_batch\_size: 8
* seed: 1996
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6


### Training results



### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 128
* eval\_batch\_size: 8
* seed: 1996
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 128
* eval\_batch\_size: 8
* seed: 1996
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #xlm-roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 128
* eval\_batch\_size: 8
* seed: 1996
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6### Training results### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0