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# electra-base-discriminator-finetuned-filtered-0602

This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1685
- Accuracy: 0.9720
- F1: 0.9721

## 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: 5e-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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results



### Framework versions

- Transformers 4.19.2
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "electra-base-discriminator-finetuned-filtered-0602", "results": []}]}
transformers pytorch electra text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #electra #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 




# electra-base-discriminator-finetuned-filtered-0602

This model is a fine-tuned version of google/electra-base-discriminator on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1685
- Accuracy: 0.9720
- F1: 0.9721

## 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: 5e-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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results



### Framework versions

- Transformers 4.19.2
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.12.1

# electra-base-discriminator-finetuned-filtered-0602

This model is a fine-tuned version of google/electra-base-discriminator on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1685
- Accuracy: 0.9720
- F1: 0.9721 ## 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: 5e-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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10 ### Training results ### Framework versions

- Transformers 4.19.2
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #electra #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # electra-base-discriminator-finetuned-filtered-0602

This model is a fine-tuned version of google/electra-base-discriminator on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1685
- Accuracy: 0.9720
- F1: 0.9721 ## 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: 5e-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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10 ### Training results ### Framework versions

- Transformers 4.19.2
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #electra #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# electra-base-discriminator-finetuned-filtered-0602

This model is a fine-tuned version of google/electra-base-discriminator on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1685
- Accuracy: 0.9720
- F1: 0.9721## 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: 5e-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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10### Training results### Framework versions

- Transformers 4.19.2
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.12.1