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# twisent_twisent

This model is a fine-tuned version of [siebert/sentiment-roberta-large-english](https://huggingface.co/siebert/sentiment-roberta-large-english) on an unknown 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results



### Framework versions

- Transformers 4.19.4
- Pytorch 1.9.0+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "twisent_twisent", "results": []}]}
transformers pytorch roberta text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 




# twisent_twisent

This model is a fine-tuned version of siebert/sentiment-roberta-large-english on an unknown 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results



### Framework versions

- Transformers 4.19.4
- Pytorch 1.9.0+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1

# twisent_twisent

This model is a fine-tuned version of siebert/sentiment-roberta-large-english on an unknown 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3 ### Training results ### Framework versions

- Transformers 4.19.4
- Pytorch 1.9.0+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 # twisent_twisent

This model is a fine-tuned version of siebert/sentiment-roberta-large-english on an unknown 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3 ### Training results ### Framework versions

- Transformers 4.19.4
- Pytorch 1.9.0+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
# twisent_twisent

This model is a fine-tuned version of siebert/sentiment-roberta-large-english on an unknown 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3### Training results### Framework versions

- Transformers 4.19.4
- Pytorch 1.9.0+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1