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# distilbert-fa-zwnj-base-finetuned-pquad

This model is a fine-tuned version of [HooshvareLab/distilbert-fa-zwnj-base](https://huggingface.co/HooshvareLab/distilbert-fa-zwnj-base) on the pquad dataset.

## Results

### Test set
| name  | value |
 ----- | ----- |
'exact' | 66.38340414896275,
'f1'| 80.23760220987583,
'total'| 8002,
'HasAns_exact'| 60.13469119579501,
'HasAns_f1'| 78.34449620292781,
'HasAns_total'| 6088,
'NoAns_exact'| 86.25914315569489,
'NoAns_f1'| 86.25914315569489,
'NoAns_total'| 1914,
'best_exact'| 66.38340414896275,
'best_exact_thresh'| 0.0,
'best_f1'| 80.23760220987589,
'best_f1_thresh'| 0.0

### Validation set
| name  | value |
 ----- | ----- |
'exact'| 64.65646940822468,
'f1'| 78.88641788270802,
'total'| 7976,
'HasAns_exact'| 57.54795663052544,
'HasAns_f1'| 76.4800782372771,
'HasAns_total'| 5995,
'NoAns_exact'| 86.16860171630489,
'NoAns_f1'| 86.16860171630489,
'NoAns_total'| 1981,
'best_exact'| 64.65646940822468,
'best_exact_thresh'| 0.0,
'best_f1'| 78.88641788270819,
'best_f1_thresh'| 0.0


## Model description

uses [distilbert-fa-zwnj-base](https://huggingface.co/HooshvareLab/distilbert-fa-zwnj-base) as base and fine-tunes it on [pquad](https://huggingface.co/datasets/Gholamreza/pquad) dataset.


## 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: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.1299        | 1.0   | 4003  | 1.1306          |
| 0.845         | 2.0   | 8006  | 1.0839          |
| 0.639         | 3.0   | 12009 | 1.1302          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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transformers pytorch tensorboard safetensors distilbert question-answering generated_from_trainer fa dataset:Gholamreza/pquad license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #distilbert #question-answering #generated_from_trainer #fa #dataset-Gholamreza/pquad #license-apache-2.0 #endpoints_compatible #region-us 

distilbert-fa-zwnj-base-finetuned-pquad
=======================================


This model is a fine-tuned version of HooshvareLab/distilbert-fa-zwnj-base on the pquad dataset.


Results
-------


### Test set



### Validation set



Model description
-----------------


uses distilbert-fa-zwnj-base as base and fine-tunes it on pquad dataset.


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: 3


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Test set ### Validation set



Model description
-----------------


uses distilbert-fa-zwnj-base as base and fine-tunes it on pquad dataset.


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: 3 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #distilbert #question-answering #generated_from_trainer #fa #dataset-Gholamreza/pquad #license-apache-2.0 #endpoints_compatible #region-us 
 ### Test set ### Validation set



Model description
-----------------


uses distilbert-fa-zwnj-base as base and fine-tunes it on pquad dataset.


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: 3 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #distilbert #question-answering #generated_from_trainer #fa #dataset-Gholamreza/pquad #license-apache-2.0 #endpoints_compatible #region-us 
### Test set### Validation set



Model description
-----------------


uses distilbert-fa-zwnj-base as base and fine-tunes it on pquad dataset.


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: 3### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2