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# pixel-base-finetuned-wnli

This model is a fine-tuned version of [Team-PIXEL/pixel-base](https://huggingface.co/Team-PIXEL/pixel-base) on the GLUE WNLI dataset.

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400
- mixed_precision_training: Apex, opt level O1

### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.12.1

{"language": ["en"], "tags": ["generated_from_trainer"], "datasets": ["glue"], "model-index": [{"name": "pixel-base-finetuned-wnli", "results": []}]}
transformers pytorch pixel text-classification generated_from_trainer en dataset:glue autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #pixel #text-classification #generated_from_trainer #en #dataset-glue #autotrain_compatible #endpoints_compatible #region-us 




# pixel-base-finetuned-wnli

This model is a fine-tuned version of Team-PIXEL/pixel-base on the GLUE WNLI dataset.

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400
- mixed_precision_training: Apex, opt level O1

### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.12.1

# pixel-base-finetuned-wnli

This model is a fine-tuned version of Team-PIXEL/pixel-base on the GLUE WNLI dataset. ## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400
- mixed_precision_training: Apex, opt level O1 ### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #pixel #text-classification #generated_from_trainer #en #dataset-glue #autotrain_compatible #endpoints_compatible #region-us 
 # pixel-base-finetuned-wnli

This model is a fine-tuned version of Team-PIXEL/pixel-base on the GLUE WNLI dataset. ## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400
- mixed_precision_training: Apex, opt level O1 ### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #pixel #text-classification #generated_from_trainer #en #dataset-glue #autotrain_compatible #endpoints_compatible #region-us 
# pixel-base-finetuned-wnli

This model is a fine-tuned version of Team-PIXEL/pixel-base on the GLUE WNLI dataset.## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400
- mixed_precision_training: Apex, opt level O1### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.12.1