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# t5-base-cnndaily

This model is a fine-tuned version of [north/t5_base_NCC_lm](https://huggingface.co/north/t5_base_NCC_lm) on the jkorsvik/cnn_daily_mail_nor_final dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.5736
- eval_rouge1: 11.7206
- eval_rouge2: 1.695
- eval_rougeL: 8.9311
- eval_rougeLsum: 10.6052
- eval_gen_len: 54.8944
- eval_runtime: 175.8203
- eval_samples_per_second: 20.197
- eval_steps_per_second: 0.631
- 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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2

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




# t5-base-cnndaily

This model is a fine-tuned version of north/t5_base_NCC_lm on the jkorsvik/cnn_daily_mail_nor_final dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.5736
- eval_rouge1: 11.7206
- eval_rouge2: 1.695
- eval_rougeL: 8.9311
- eval_rougeLsum: 10.6052
- eval_gen_len: 54.8944
- eval_runtime: 175.8203
- eval_samples_per_second: 20.197
- eval_steps_per_second: 0.631
- 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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2

# t5-base-cnndaily

This model is a fine-tuned version of north/t5_base_NCC_lm on the jkorsvik/cnn_daily_mail_nor_final dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.5736
- eval_rouge1: 11.7206
- eval_rouge2: 1.695
- eval_rougeL: 8.9311
- eval_rougeLsum: 10.6052
- eval_gen_len: 54.8944
- eval_runtime: 175.8203
- eval_samples_per_second: 20.197
- eval_steps_per_second: 0.631
- 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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0 ### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-jkorsvik/cnn_daily_mail_nor_final #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # t5-base-cnndaily

This model is a fine-tuned version of north/t5_base_NCC_lm on the jkorsvik/cnn_daily_mail_nor_final dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.5736
- eval_rouge1: 11.7206
- eval_rouge2: 1.695
- eval_rougeL: 8.9311
- eval_rougeLsum: 10.6052
- eval_gen_len: 54.8944
- eval_runtime: 175.8203
- eval_samples_per_second: 20.197
- eval_steps_per_second: 0.631
- 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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0 ### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-jkorsvik/cnn_daily_mail_nor_final #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# t5-base-cnndaily

This model is a fine-tuned version of north/t5_base_NCC_lm on the jkorsvik/cnn_daily_mail_nor_final dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.5736
- eval_rouge1: 11.7206
- eval_rouge2: 1.695
- eval_rougeL: 8.9311
- eval_rougeLsum: 10.6052
- eval_gen_len: 54.8944
- eval_runtime: 175.8203
- eval_samples_per_second: 20.197
- eval_steps_per_second: 0.631
- 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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2