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# t5-large-snl-2

This model is a fine-tuned version of [navjordj/t5-large-snl](https://huggingface.co/navjordj/t5-large-snl) on the navjordj/SNL_summarization dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.8691
- eval_rouge1: 35.1506
- eval_rouge2: 16.0888
- eval_rougeL: 29.7007
- eval_rougeLsum: 32.4251
- eval_gen_len: 41.5629
- eval_runtime: 261.235
- eval_samples_per_second: 3.135
- eval_steps_per_second: 0.199
- 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: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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": ["generated_from_trainer"], "datasets": ["navjordj/SNL_summarization"], "inference": {"parameters": {"max_length": 160, "repetition_penalty": 1.2}}, "model-index": [{"name": "t5-large-snl-2", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "snl-summarization", "type": "snl-summarization"}, "metrics": [{"type": "rouge", "value": 35.1506, "name": "Rouge1"}]}]}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:navjordj/SNL_summarization model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-navjordj/SNL_summarization #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# t5-large-snl-2

This model is a fine-tuned version of navjordj/t5-large-snl on the navjordj/SNL_summarization dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.8691
- eval_rouge1: 35.1506
- eval_rouge2: 16.0888
- eval_rougeL: 29.7007
- eval_rougeLsum: 32.4251
- eval_gen_len: 41.5629
- eval_runtime: 261.235
- eval_samples_per_second: 3.135
- eval_steps_per_second: 0.199
- 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: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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-large-snl-2

This model is a fine-tuned version of navjordj/t5-large-snl on the navjordj/SNL_summarization dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.8691
- eval_rouge1: 35.1506
- eval_rouge2: 16.0888
- eval_rougeL: 29.7007
- eval_rougeLsum: 32.4251
- eval_gen_len: 41.5629
- eval_runtime: 261.235
- eval_samples_per_second: 3.135
- eval_steps_per_second: 0.199
- 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: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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-navjordj/SNL_summarization #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # t5-large-snl-2

This model is a fine-tuned version of navjordj/t5-large-snl on the navjordj/SNL_summarization dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.8691
- eval_rouge1: 35.1506
- eval_rouge2: 16.0888
- eval_rougeL: 29.7007
- eval_rougeLsum: 32.4251
- eval_gen_len: 41.5629
- eval_runtime: 261.235
- eval_samples_per_second: 3.135
- eval_steps_per_second: 0.199
- 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: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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-navjordj/SNL_summarization #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# t5-large-snl-2

This model is a fine-tuned version of navjordj/t5-large-snl on the navjordj/SNL_summarization dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.8691
- eval_rouge1: 35.1506
- eval_rouge2: 16.0888
- eval_rougeL: 29.7007
- eval_rougeLsum: 32.4251
- eval_gen_len: 41.5629
- eval_runtime: 261.235
- eval_samples_per_second: 3.135
- eval_steps_per_second: 0.199
- 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: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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