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# cnn_news_summary_reduced

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.7174
- eval_rouge1: 0.2449
- eval_rouge2: 0.1201
- eval_rougeL: 0.2041
- eval_rougeLsum: 0.2043
- eval_gen_len: 19.0
- eval_runtime: 168.435
- eval_samples_per_second: 15.876
- eval_steps_per_second: 0.997
- epoch: 1.0
- step: 669

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["cnn_dailymail"], "model-index": [{"name": "cnn_news_summary_reduced", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer dataset:cnn_dailymail license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# cnn_news_summary_reduced

This model is a fine-tuned version of t5-small on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.7174
- eval_rouge1: 0.2449
- eval_rouge2: 0.1201
- eval_rougeL: 0.2041
- eval_rougeLsum: 0.2043
- eval_gen_len: 19.0
- eval_runtime: 168.435
- eval_samples_per_second: 15.876
- eval_steps_per_second: 0.997
- epoch: 1.0
- step: 669

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

# cnn_news_summary_reduced

This model is a fine-tuned version of t5-small on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.7174
- eval_rouge1: 0.2449
- eval_rouge2: 0.1201
- eval_rougeL: 0.2041
- eval_rougeLsum: 0.2043
- eval_gen_len: 19.0
- eval_runtime: 168.435
- eval_samples_per_second: 15.876
- eval_steps_per_second: 0.997
- epoch: 1.0
- step: 669 ## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # cnn_news_summary_reduced

This model is a fine-tuned version of t5-small on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.7174
- eval_rouge1: 0.2449
- eval_rouge2: 0.1201
- eval_rougeL: 0.2041
- eval_rougeLsum: 0.2043
- eval_gen_len: 19.0
- eval_runtime: 168.435
- eval_samples_per_second: 15.876
- eval_steps_per_second: 0.997
- epoch: 1.0
- step: 669 ## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# cnn_news_summary_reduced

This model is a fine-tuned version of t5-small on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.7174
- eval_rouge1: 0.2449
- eval_rouge2: 0.1201
- eval_rougeL: 0.2041
- eval_rougeLsum: 0.2043
- eval_gen_len: 19.0
- eval_runtime: 168.435
- eval_samples_per_second: 15.876
- eval_steps_per_second: 0.997
- epoch: 1.0
- step: 669## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3