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# commitRoBertaWhy

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: 1.7709
- Accuracy: 0.7818

## 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: 5e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 483  | 0.4784          | 0.7515   |
| 0.5809        | 2.0   | 966  | 0.7377          | 0.7636   |
| 0.5228        | 3.0   | 1449 | 0.9487          | 0.7879   |
| 0.5178        | 4.0   | 1932 | 0.7810          | 0.8061   |
| 0.4931        | 5.0   | 2415 | 0.8674          | 0.8182   |
| 0.4562        | 6.0   | 2898 | 0.8308          | 0.8121   |
| 0.4585        | 7.0   | 3381 | 1.2448          | 0.7818   |
| 0.3061        | 8.0   | 3864 | 1.0845          | 0.8061   |
| 0.3341        | 9.0   | 4347 | 1.1429          | 0.7879   |
| 0.288         | 10.0  | 4830 | 1.0559          | 0.8242   |
| 0.2673        | 11.0  | 5313 | 1.2845          | 0.8      |
| 0.1954        | 12.0  | 5796 | 1.4496          | 0.8      |
| 0.227         | 13.0  | 6279 | 1.3763          | 0.8      |
| 0.1761        | 14.0  | 6762 | 1.4341          | 0.8061   |
| 0.2154        | 15.0  | 7245 | 1.3411          | 0.8061   |
| 0.1736        | 16.0  | 7728 | 1.4826          | 0.7879   |
| 0.0983        | 17.0  | 8211 | 1.7190          | 0.7818   |
| 0.1382        | 18.0  | 8694 | 1.5242          | 0.8      |
| 0.1262        | 19.0  | 9177 | 1.6978          | 0.7879   |
| 0.0962        | 20.0  | 9660 | 1.7709          | 0.7818   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

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

commitRoBertaWhy
================


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: 1.7709
* Accuracy: 0.7818


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: 5e-06
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-06
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
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: 5e-06
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3