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# t5-small-finetuned-amazon-en

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.1622
- eval_rouge1: 14.7056
- eval_rouge2: 6.5373
- eval_rougeL: 13.8753
- eval_rougeLsum: 13.9924
- eval_runtime: 3.8484
- eval_samples_per_second: 35.08
- eval_steps_per_second: 4.417
- 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

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




# t5-small-finetuned-amazon-en

This model is a fine-tuned version of t5-small on the amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.1622
- eval_rouge1: 14.7056
- eval_rouge2: 6.5373
- eval_rougeL: 13.8753
- eval_rougeLsum: 13.9924
- eval_runtime: 3.8484
- eval_samples_per_second: 35.08
- eval_steps_per_second: 4.417
- 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

# t5-small-finetuned-amazon-en

This model is a fine-tuned version of t5-small on the amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.1622
- eval_rouge1: 14.7056
- eval_rouge2: 6.5373
- eval_rougeL: 13.8753
- eval_rougeLsum: 13.9924
- eval_runtime: 3.8484
- eval_samples_per_second: 35.08
- eval_steps_per_second: 4.417
- 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100 ### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #summarization #generated_from_trainer #dataset-amazon_reviews_multi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # t5-small-finetuned-amazon-en

This model is a fine-tuned version of t5-small on the amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.1622
- eval_rouge1: 14.7056
- eval_rouge2: 6.5373
- eval_rougeL: 13.8753
- eval_rougeLsum: 13.9924
- eval_runtime: 3.8484
- eval_samples_per_second: 35.08
- eval_steps_per_second: 4.417
- 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100 ### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #summarization #generated_from_trainer #dataset-amazon_reviews_multi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# t5-small-finetuned-amazon-en

This model is a fine-tuned version of t5-small on the amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.1622
- eval_rouge1: 14.7056
- eval_rouge2: 6.5373
- eval_rougeL: 13.8753
- eval_rougeLsum: 13.9924
- eval_runtime: 3.8484
- eval_samples_per_second: 35.08
- eval_steps_per_second: 4.417
- 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2