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# parsbert-finetuned-pos

This model is a fine-tuned version of [HooshvareLab/bert-base-parsbert-uncased](https://huggingface.co/HooshvareLab/bert-base-parsbert-uncased) on the udpos28 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1385
- Precision: 0.9448
- Recall: 0.9486
- F1: 0.9467
- Accuracy: 0.9599

## 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: 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.122         | 1.0   | 3103 | 0.1215          | 0.9363    | 0.9424 | 0.9394 | 0.9561   |
| 0.0735        | 2.0   | 6206 | 0.1297          | 0.9413    | 0.9474 | 0.9443 | 0.9582   |
| 0.0373        | 3.0   | 9309 | 0.1385          | 0.9448    | 0.9486 | 0.9467 | 0.9599   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0
- Datasets 2.0.0
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "datasets": ["udpos28"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "parsbert-finetuned-pos", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "udpos28", "type": "udpos28", "args": "fa"}, "metrics": [{"type": "precision", "value": 0.9447937270415372, "name": "Precision"}, {"type": "recall", "value": 0.9486470191864382, "name": "Recall"}, {"type": "f1", "value": 0.9467164522465448, "name": "F1"}, {"type": "accuracy", "value": 0.9598951738759165, "name": "Accuracy"}]}]}]}
transformers pytorch bert token-classification generated_from_trainer dataset:udpos28 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #dataset-udpos28 #model-index #autotrain_compatible #endpoints_compatible #region-us 

parsbert-finetuned-pos
======================


This model is a fine-tuned version of HooshvareLab/bert-base-parsbert-uncased on the udpos28 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1385
* Precision: 0.9448
* Recall: 0.9486
* F1: 0.9467
* Accuracy: 0.9599


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: 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: 3


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0
* Datasets 2.0.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 3 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0
* Datasets 2.0.0
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #dataset-udpos28 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 3 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0
* Datasets 2.0.0
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #dataset-udpos28 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 3### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0
* Datasets 2.0.0
* Tokenizers 0.11.6