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# text-summarization-bart-large-cnn-three-percent

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the cnn_dailymail 3.0.0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.7193
- eval_rouge1: 44.586
- eval_rouge2: 21.4773
- eval_rougeL: 31.0223
- eval_rougeLsum: 41.5275
- eval_gen_len: 83.8787
- eval_runtime: 16880.3832
- eval_samples_per_second: 0.792
- eval_steps_per_second: 0.396
- step: 0

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 0.3

### Framework versions

- Transformers 4.28.0
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["cnn_dailymail"], "model-index": [{"name": "text-summarization-bart-large-cnn-three-percent", "results": []}]}
transformers pytorch tensorboard bart text2text-generation generated_from_trainer dataset:cnn_dailymail license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #license-mit #autotrain_compatible #endpoints_compatible #region-us 




# text-summarization-bart-large-cnn-three-percent

This model is a fine-tuned version of facebook/bart-large-cnn on the cnn_dailymail 3.0.0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.7193
- eval_rouge1: 44.586
- eval_rouge2: 21.4773
- eval_rougeL: 31.0223
- eval_rougeLsum: 41.5275
- eval_gen_len: 83.8787
- eval_runtime: 16880.3832
- eval_samples_per_second: 0.792
- eval_steps_per_second: 0.396
- step: 0

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 0.3

### Framework versions

- Transformers 4.28.0
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

# text-summarization-bart-large-cnn-three-percent

This model is a fine-tuned version of facebook/bart-large-cnn on the cnn_dailymail 3.0.0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.7193
- eval_rouge1: 44.586
- eval_rouge2: 21.4773
- eval_rougeL: 31.0223
- eval_rougeLsum: 41.5275
- eval_gen_len: 83.8787
- eval_runtime: 16880.3832
- eval_samples_per_second: 0.792
- eval_steps_per_second: 0.396
- step: 0 ## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 0.3 ### Framework versions

- Transformers 4.28.0
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 # text-summarization-bart-large-cnn-three-percent

This model is a fine-tuned version of facebook/bart-large-cnn on the cnn_dailymail 3.0.0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.7193
- eval_rouge1: 44.586
- eval_rouge2: 21.4773
- eval_rougeL: 31.0223
- eval_rougeLsum: 41.5275
- eval_gen_len: 83.8787
- eval_runtime: 16880.3832
- eval_samples_per_second: 0.792
- eval_steps_per_second: 0.396
- step: 0 ## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 0.3 ### Framework versions

- Transformers 4.28.0
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3