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# finetuned_roberta-base-uncased

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4799
- Accuracy: 0.6519

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.372         | 1.0   | 102  | 1.3643          | 0.3375   |
| 1.1591        | 2.0   | 204  | 1.1988          | 0.4830   |
| 0.9623        | 3.0   | 306  | 1.0802          | 0.5694   |
| 0.7766        | 4.0   | 408  | 0.9885          | 0.6237   |
| 0.7336        | 5.0   | 510  | 1.0393          | 0.6120   |
| 0.6284        | 6.0   | 612  | 1.1150          | 0.6392   |
| 0.3616        | 7.0   | 714  | 1.2183          | 0.6402   |
| 0.3526        | 8.0   | 816  | 1.2362          | 0.6305   |
| 0.3151        | 9.0   | 918  | 1.3058          | 0.6372   |
| 0.3035        | 10.0  | 1020 | 1.2966          | 0.6343   |
| 0.2458        | 11.0  | 1122 | 1.3752          | 0.6508   |
| 0.2469        | 12.0  | 1224 | 1.4557          | 0.6557   |
| 0.2039        | 13.0  | 1326 | 1.5541          | 0.6372   |
| 0.1691        | 14.0  | 1428 | 1.5308          | 0.6343   |
| 0.1455        | 15.0  | 1530 | 1.6339          | 0.6421   |
| 0.1716        | 16.0  | 1632 | 1.6843          | 0.6392   |
| 0.1698        | 17.0  | 1734 | 1.6802          | 0.6479   |
| 0.2009        | 18.0  | 1836 | 1.6544          | 0.6479   |
| 0.1415        | 19.0  | 1938 | 1.6759          | 0.6518   |
| 0.1616        | 20.0  | 2040 | 1.6833          | 0.6508   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "finetuned_roberta-base-uncased", "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 

finetuned\_roberta-base-uncased
===============================


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


* Loss: 1.4799
* Accuracy: 0.6519


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
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: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
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: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2