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# bart-qa10k-10

This model is a fine-tuned version of [shrinath-suresh/bart-qa10k](https://huggingface.co/shrinath-suresh/bart-qa10k) on the shrinath-suresh/qa-10k 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["shrinath-suresh/qa-10k"], "model-index": [{"name": "bart-qa10k-10", "results": []}]}
transformers pytorch bart text2text-generation generated_from_trainer dataset:shrinath-suresh/qa-10k license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #dataset-shrinath-suresh/qa-10k #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 




# bart-qa10k-10

This model is a fine-tuned version of shrinath-suresh/bart-qa10k on the shrinath-suresh/qa-10k 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.0
- Tokenizers 0.13.2

# bart-qa10k-10

This model is a fine-tuned version of shrinath-suresh/bart-qa10k on the shrinath-suresh/qa-10k 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8.0
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #dataset-shrinath-suresh/qa-10k #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # bart-qa10k-10

This model is a fine-tuned version of shrinath-suresh/bart-qa10k on the shrinath-suresh/qa-10k 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8.0
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.0
- Tokenizers 0.13.2