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# bert-base-parsbert-uncased-finetuned-khorshid-accelerate

This model is a fine-tuned version of [HooshvareLab/bert-base-parsbert-uncased](https://huggingface.co/HooshvareLab/bert-base-parsbert-uncased) on [a sentiment analysis dataset of Hala-Khorshid T.V program](https://drive.google.com/file/d/1vztWibWDCeiueAqhl91hbJnQblskQkPq/view?usp=sharing) dataset.
We used 🤗 Accelerate to train the model.

## 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: 3.0

### Training results

More information needed


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "model-index": [{"name": "bert-base-parsbert-uncased-finetuned-khorshid-accelerate", "results": []}]}
transformers pytorch bert fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 




# bert-base-parsbert-uncased-finetuned-khorshid-accelerate

This model is a fine-tuned version of HooshvareLab/bert-base-parsbert-uncased on a sentiment analysis dataset of Hala-Khorshid T.V program dataset.
We used  Accelerate to train the model.

## 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: 3.0

### Training results

More information needed


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2

# bert-base-parsbert-uncased-finetuned-khorshid-accelerate

This model is a fine-tuned version of HooshvareLab/bert-base-parsbert-uncased on a sentiment analysis dataset of Hala-Khorshid T.V program dataset.
We used  Accelerate to train the model. ## 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: 3.0 ### Training results

More information needed ### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 # bert-base-parsbert-uncased-finetuned-khorshid-accelerate

This model is a fine-tuned version of HooshvareLab/bert-base-parsbert-uncased on a sentiment analysis dataset of Hala-Khorshid T.V program dataset.
We used  Accelerate to train the model. ## 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: 3.0 ### Training results

More information needed ### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
# bert-base-parsbert-uncased-finetuned-khorshid-accelerate

This model is a fine-tuned version of HooshvareLab/bert-base-parsbert-uncased on a sentiment analysis dataset of Hala-Khorshid T.V program dataset.
We used  Accelerate to train the model.## 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: 3.0### Training results

More information needed### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2