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# xlm-roberta-large-finetuned-code-mixed-DS

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7328
- Accuracy: 0.7022
- Precision: 0.6437
- Recall: 0.6634
- F1: 0.6483

## 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: 8
- eval_batch_size: 16
- seed: 43
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.098         | 0.5   | 248  | 1.0944          | 0.5352   | 0.2355    | 0.3344 | 0.2397 |
| 1.0827        | 1.0   | 496  | 1.0957          | 0.5352   | 0.5789    | 0.3379 | 0.2502 |
| 1.0503        | 1.5   | 744  | 0.9969          | 0.5312   | 0.3621    | 0.4996 | 0.3914 |
| 0.9728        | 2.0   | 992  | 0.8525          | 0.6056   | 0.5096    | 0.5565 | 0.4678 |
| 0.9271        | 2.49  | 1240 | 0.7809          | 0.6378   | 0.6014    | 0.6320 | 0.5963 |
| 0.7977        | 2.99  | 1488 | 0.8290          | 0.5875   | 0.5630    | 0.5918 | 0.5390 |
| 0.752         | 3.49  | 1736 | 0.7684          | 0.7123   | 0.6526    | 0.6610 | 0.6558 |
| 0.6846        | 3.99  | 1984 | 0.7328          | 0.7022   | 0.6437    | 0.6634 | 0.6483 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "model-index": [{"name": "xlm-roberta-large-finetuned-code-mixed-DS", "results": []}]}
transformers pytorch xlm-roberta text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

xlm-roberta-large-finetuned-code-mixed-DS
=========================================


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


* Loss: 0.7328
* Accuracy: 0.7022
* Precision: 0.6437
* Recall: 0.6634
* F1: 0.6483


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: 8
* eval\_batch\_size: 16
* seed: 43
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.1+cu111
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 43
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.1+cu111
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #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: 8
* eval\_batch\_size: 16
* seed: 43
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.1+cu111
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #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: 8
* eval\_batch\_size: 16
* seed: 43
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.1+cu111
* Datasets 2.3.2
* Tokenizers 0.12.1