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# xlm-roberta-base-finetuned-panx-en-custom

This model is a fine-tuned version of [maren-hugg/xlm-roberta-base-finetuned-panx-en](https://huggingface.co/maren-hugg/xlm-roberta-base-finetuned-panx-en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1045
- F1: 0.8782
- Precision: 0.8496
- Recall: 0.9088
- Accuracy: 0.9754

## 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: 4.886597454037411e-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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
| 0.128         | 0.75  | 24   | 0.1087          | 0.8514 | 0.8299    | 0.8740 | 0.9713   |
| 0.074         | 1.5   | 48   | 0.1006          | 0.8637 | 0.8505    | 0.8773 | 0.9750   |
| 0.0506        | 2.25  | 72   | 0.0987          | 0.8728 | 0.8587    | 0.8872 | 0.9749   |
| 0.0393        | 3.0   | 96   | 0.1045          | 0.8782 | 0.8496    | 0.9088 | 0.9754   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1", "precision", "recall", "accuracy"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-en-custom", "results": []}]}
transformers pytorch tensorboard xlm-roberta token-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

xlm-roberta-base-finetuned-panx-en-custom
=========================================


This model is a fine-tuned version of maren-hugg/xlm-roberta-base-finetuned-panx-en on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1045
* F1: 0.8782
* Precision: 0.8496
* Recall: 0.9088
* Accuracy: 0.9754


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: 4.886597454037411e-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: 3


### Training results



### Framework versions


* Transformers 4.30.2
* Pytorch 2.0.1+cu118
* Datasets 2.13.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4.886597454037411e-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: 3 ### Training results ### Framework versions


* Transformers 4.30.2
* Pytorch 2.0.1+cu118
* Datasets 2.13.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4.886597454037411e-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: 3 ### Training results ### Framework versions


* Transformers 4.30.2
* Pytorch 2.0.1+cu118
* Datasets 2.13.0
* Tokenizers 0.13.3