
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# xlm-roberta-base-finetuned-peyma-fa

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: 0.0937
- F1: 0.9249

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1562        | 1.0   | 998  | 0.0691          | 0.8777 |
| 0.0638        | 2.0   | 1996 | 0.0703          | 0.8908 |
| 0.0457        | 3.0   | 2994 | 0.0645          | 0.8975 |
| 0.0281        | 4.0   | 3992 | 0.0842          | 0.8994 |
| 0.0206        | 5.0   | 4990 | 0.0651          | 0.9164 |
| 0.0139        | 6.0   | 5988 | 0.0787          | 0.9148 |
| 0.0083        | 7.0   | 6986 | 0.0838          | 0.9253 |
| 0.0052        | 8.0   | 7984 | 0.0833          | 0.9221 |
| 0.0031        | 9.0   | 8982 | 0.0947          | 0.9230 |
| 0.0028        | 10.0  | 9980 | 0.0937          | 0.9249 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.9.1
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "xlm-roberta-base-finetuned-peyma-fa", "results": []}]}
transformers pytorch tensorboard xlm-roberta token-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us 

xlm-roberta-base-finetuned-peyma-fa
===================================


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: 0.0937
* F1: 0.9249


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-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.9.1
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.9.1
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.9.1
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #xlm-roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.9.1
* Datasets 2.1.0
* Tokenizers 0.12.1