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# QuBERTa-finetuned-pos

This model is a fine-tuned version of [Llamacha/QuBERTa](https://huggingface.co/Llamacha/QuBERTa) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4249
- Precision: 0.8372
- Recall: 0.8702
- F1: 0.8534
- Accuracy: 0.8623

## 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: 16
- eval_batch_size: 16
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 152  | 0.6146          | 0.6876    | 0.7482 | 0.7167 | 0.7360   |
| No log        | 2.0   | 304  | 0.4937          | 0.7554    | 0.8041 | 0.7790 | 0.7932   |
| No log        | 3.0   | 456  | 0.4525          | 0.7920    | 0.8238 | 0.8076 | 0.8200   |
| 0.5624        | 4.0   | 608  | 0.4294          | 0.8144    | 0.8426 | 0.8283 | 0.8391   |
| 0.5624        | 5.0   | 760  | 0.4245          | 0.8192    | 0.8521 | 0.8353 | 0.8445   |
| 0.5624        | 6.0   | 912  | 0.4357          | 0.8201    | 0.8607 | 0.8399 | 0.8480   |
| 0.3064        | 7.0   | 1064 | 0.4240          | 0.8308    | 0.8694 | 0.8497 | 0.8582   |
| 0.3064        | 8.0   | 1216 | 0.4231          | 0.8406    | 0.8757 | 0.8578 | 0.8653   |
| 0.3064        | 9.0   | 1368 | 0.4202          | 0.8389    | 0.8686 | 0.8535 | 0.8617   |
| 0.2227        | 10.0  | 1520 | 0.4249          | 0.8372    | 0.8702 | 0.8534 | 0.8623   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "QuBERTa-finetuned-pos", "results": []}]}
transformers pytorch roberta token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

QuBERTa-finetuned-pos
=====================


This model is a fine-tuned version of Llamacha/QuBERTa on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4249
* Precision: 0.8372
* Recall: 0.8702
* F1: 0.8534
* Accuracy: 0.8623


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: 16
* eval\_batch\_size: 16
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6