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# outputs

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the cnn_dailymail 3.0.0 dataset.

## Model description

More information needed

## Intended uses & limitations

This is a work in progress. Please don't use these weights.

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: IPU
- gradient_accumulation_steps: 256
- total_train_batch_size: 2048
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 2.0
- training precision: Mixed Precision

### Training results



### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cpu
- Datasets 2.2.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["cnn_dailymail"], "model-index": [{"name": "outputs", "results": []}]}
transformers pytorch optimum_graphcore bart text2text-generation generated_from_trainer dataset:cnn_dailymail license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #optimum_graphcore #bart #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 




# outputs

This model is a fine-tuned version of facebook/bart-large on the cnn_dailymail 3.0.0 dataset.

## Model description

More information needed

## Intended uses & limitations

This is a work in progress. Please don't use these weights.

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: IPU
- gradient_accumulation_steps: 256
- total_train_batch_size: 2048
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 2.0
- training precision: Mixed Precision

### Training results



### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cpu
- Datasets 2.2.1
- Tokenizers 0.12.1

# outputs

This model is a fine-tuned version of facebook/bart-large on the cnn_dailymail 3.0.0 dataset. ## Model description

More information needed ## Intended uses & limitations

This is a work in progress. Please don't use these weights. ## Training and evaluation data

More information needed ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: IPU
- gradient_accumulation_steps: 256
- total_train_batch_size: 2048
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 2.0
- training precision: Mixed Precision ### Training results ### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cpu
- Datasets 2.2.1
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #optimum_graphcore #bart #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # outputs

This model is a fine-tuned version of facebook/bart-large on the cnn_dailymail 3.0.0 dataset. ## Model description

More information needed ## Intended uses & limitations

This is a work in progress. Please don't use these weights. ## Training and evaluation data

More information needed ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: IPU
- gradient_accumulation_steps: 256
- total_train_batch_size: 2048
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 2.0
- training precision: Mixed Precision ### Training results ### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cpu
- Datasets 2.2.1
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #optimum_graphcore #bart #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# outputs

This model is a fine-tuned version of facebook/bart-large on the cnn_dailymail 3.0.0 dataset.## Model description

More information needed## Intended uses & limitations

This is a work in progress. Please don't use these weights.## Training and evaluation data

More information needed## Training procedure### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: IPU
- gradient_accumulation_steps: 256
- total_train_batch_size: 2048
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 2.0
- training precision: Mixed Precision### Training results### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cpu
- Datasets 2.2.1
- Tokenizers 0.12.1