

# tst-summarization

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6972
- Rouge1: 44.9509
- Rouge2: 21.7162
- Rougel: 37.7582
- Rougelsum: 41.7239
- Gen Len: 22.7714

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cpu
- Datasets 2.8.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["samsum"], "metrics": ["rouge"], "model-index": [{"name": "tst-summarization", "results": [{"task": {"type": "summarization", "name": "Summarization"}, "dataset": {"name": "samsum", "type": "samsum", "config": "samsum", "split": "train", "args": "samsum"}, "metrics": [{"type": "rouge", "value": 44.9509, "name": "Rouge1"}]}]}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:samsum license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 



# tst-summarization

This model is a fine-tuned version of t5-small on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6972
- Rouge1: 44.9509
- Rouge2: 21.7162
- Rougel: 37.7582
- Rougelsum: 41.7239
- Gen Len: 22.7714

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cpu
- Datasets 2.8.0
- Tokenizers 0.13.2

# tst-summarization

This model is a fine-tuned version of t5-small on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6972
- Rouge1: 44.9509
- Rouge2: 21.7162
- Rougel: 37.7582
- Rougelsum: 41.7239
- Gen Len: 22.7714 ## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cpu
- Datasets 2.8.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # tst-summarization

This model is a fine-tuned version of t5-small on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6972
- Rouge1: 44.9509
- Rouge2: 21.7162
- Rougel: 37.7582
- Rougelsum: 41.7239
- Gen Len: 22.7714 ## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cpu
- Datasets 2.8.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# tst-summarization

This model is a fine-tuned version of t5-small on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6972
- Rouge1: 44.9509
- Rouge2: 21.7162
- Rougel: 37.7582
- Rougelsum: 41.7239
- Gen Len: 22.7714## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0### Training results### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cpu
- Datasets 2.8.0
- Tokenizers 0.13.2