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# albert-puncapital

This model is a fine-tuned version of [indobert-lite-base-p2](https://huggingface.co/indobert-lite-base-p2) 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "albert-puncapital", "results": []}]}
transformers pytorch albert token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #albert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 




# albert-puncapital

This model is a fine-tuned version of indobert-lite-base-p2 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1

# albert-puncapital

This model is a fine-tuned version of indobert-lite-base-p2 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #albert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 # albert-puncapital

This model is a fine-tuned version of indobert-lite-base-p2 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #albert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
# albert-puncapital

This model is a fine-tuned version of indobert-lite-base-p2 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP### Training results### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1