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# xlm-roberta-large-en-si-only-finetuned-sinquad-v12

This model is a fine-tuned version of [9wimu9/xlm-roberta-large-en-si-only](https://huggingface.co/9wimu9/xlm-roberta-large-en-si-only) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7128

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.612         | 1.0   | 93   | 0.8081          |
| 0.7979        | 2.0   | 186  | 0.6823          |
| 0.6887        | 3.0   | 279  | 0.6532          |
| 0.4166        | 4.0   | 372  | 0.6846          |
| 0.3985        | 5.0   | 465  | 0.7128          |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.6.1
- Tokenizers 0.12.1

{'exact_match': 69.58841463414635, 'f1': 87.9274817360267}
{"tags": ["generated_from_trainer"], "model-index": [{"name": "xlm-roberta-large-en-si-only-finetuned-sinquad-v12", "results": []}]}
transformers pytorch safetensors xlm-roberta question-answering generated_from_trainer endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #safetensors #xlm-roberta #question-answering #generated_from_trainer #endpoints_compatible #has_space #region-us 

xlm-roberta-large-en-si-only-finetuned-sinquad-v12
==================================================


This model is a fine-tuned version of 9wimu9/xlm-roberta-large-en-si-only on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.7128


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: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 1.12.1+cu116
* Datasets 2.6.1
* Tokenizers 0.12.1


{'exact\_match': 69.58841463414635, 'f1': 87.9274817360267}



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 1.12.1+cu116
* Datasets 2.6.1
* Tokenizers 0.12.1


{'exact\_match': 69.58841463414635, 'f1': 87.9274817360267}
TAGS
#transformers #pytorch #safetensors #xlm-roberta #question-answering #generated_from_trainer #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 1.12.1+cu116
* Datasets 2.6.1
* Tokenizers 0.12.1


{'exact\_match': 69.58841463414635, 'f1': 87.9274817360267}