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# esberto-small

This model is a fine-tuned version of [](https://huggingface.co/) on the oscar 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.10.0.dev0
- Pytorch 1.9.0+cu102
- Datasets 1.10.3.dev0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "datasets": ["oscar"], "model_index": [{"name": "esberto-small", "results": [{"task": {"name": "Masked Language Modeling", "type": "fill-mask"}, "dataset": {"name": "oscar", "type": "oscar", "args": "unshuffled_original_eo"}}]}]}
transformers pytorch tensorboard roberta fill-mask generated_from_trainer dataset:oscar autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #fill-mask #generated_from_trainer #dataset-oscar #autotrain_compatible #endpoints_compatible #region-us 




# esberto-small

This model is a fine-tuned version of [](URL on the oscar 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.10.0.dev0
- Pytorch 1.9.0+cu102
- Datasets 1.10.3.dev0
- Tokenizers 0.10.3

# esberto-small

This model is a fine-tuned version of [](URL on the oscar 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1 ### Training results ### Framework versions

- Transformers 4.10.0.dev0
- Pytorch 1.9.0+cu102
- Datasets 1.10.3.dev0
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #roberta #fill-mask #generated_from_trainer #dataset-oscar #autotrain_compatible #endpoints_compatible #region-us 
 # esberto-small

This model is a fine-tuned version of [](URL on the oscar 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1 ### Training results ### Framework versions

- Transformers 4.10.0.dev0
- Pytorch 1.9.0+cu102
- Datasets 1.10.3.dev0
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #roberta #fill-mask #generated_from_trainer #dataset-oscar #autotrain_compatible #endpoints_compatible #region-us 
# esberto-small

This model is a fine-tuned version of [](URL on the oscar 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1### Training results### Framework versions

- Transformers 4.10.0.dev0
- Pytorch 1.9.0+cu102
- Datasets 1.10.3.dev0
- Tokenizers 0.10.3