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# kobigbird-pure2-93753787

This model is a fine-tuned version of [monologg/kobigbird-bert-base](https://huggingface.co/monologg/kobigbird-bert-base) on the custom_squad_v2 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.4619
- eval_runtime: 26.5163
- eval_samples_per_second: 45.406
- eval_steps_per_second: 0.717
- epoch: 0.99
- step: 21

## 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: 64
- seed: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1

{"tags": ["generated_from_trainer"], "datasets": ["custom_squad_v2"], "model-index": [{"name": "kobigbird-pure2-93753787", "results": []}]}
transformers pytorch tensorboard big_bird question-answering generated_from_trainer dataset:custom_squad_v2 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #big_bird #question-answering #generated_from_trainer #dataset-custom_squad_v2 #endpoints_compatible #region-us 




# kobigbird-pure2-93753787

This model is a fine-tuned version of monologg/kobigbird-bert-base on the custom_squad_v2 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.4619
- eval_runtime: 26.5163
- eval_samples_per_second: 45.406
- eval_steps_per_second: 0.717
- epoch: 0.99
- step: 21

## 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: 64
- seed: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1

# kobigbird-pure2-93753787

This model is a fine-tuned version of monologg/kobigbird-bert-base on the custom_squad_v2 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.4619
- eval_runtime: 26.5163
- eval_samples_per_second: 45.406
- eval_steps_per_second: 0.717
- epoch: 0.99
- step: 21 ## 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: 64
- seed: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1
TAGS
#transformers #pytorch #tensorboard #big_bird #question-answering #generated_from_trainer #dataset-custom_squad_v2 #endpoints_compatible #region-us 
 # kobigbird-pure2-93753787

This model is a fine-tuned version of monologg/kobigbird-bert-base on the custom_squad_v2 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.4619
- eval_runtime: 26.5163
- eval_samples_per_second: 45.406
- eval_steps_per_second: 0.717
- epoch: 0.99
- step: 21 ## 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: 64
- seed: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1
TAGS
#transformers #pytorch #tensorboard #big_bird #question-answering #generated_from_trainer #dataset-custom_squad_v2 #endpoints_compatible #region-us 
# kobigbird-pure2-93753787

This model is a fine-tuned version of monologg/kobigbird-bert-base on the custom_squad_v2 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.4619
- eval_runtime: 26.5163
- eval_samples_per_second: 45.406
- eval_steps_per_second: 0.717
- epoch: 0.99
- step: 21## 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: 64
- seed: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1