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# t5-small-finetuned-amazon-en-fr

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.9766
- eval_rouge1: 0.1418
- eval_rouge2: 0.0716
- eval_rougeL: 0.1369
- eval_rougeLsum: 0.1383
- eval_runtime: 5.36
- eval_samples_per_second: 52.426
- eval_steps_per_second: 6.716
- epoch: 2.0
- step: 2798

## 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: 3

### Framework versions

- Transformers 4.22.1
- Pytorch 1.12.1+cu102
- Datasets 2.9.0
- Tokenizers 0.12.1

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




# t5-small-finetuned-amazon-en-fr

This model is a fine-tuned version of t5-small on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.9766
- eval_rouge1: 0.1418
- eval_rouge2: 0.0716
- eval_rougeL: 0.1369
- eval_rougeLsum: 0.1383
- eval_runtime: 5.36
- eval_samples_per_second: 52.426
- eval_steps_per_second: 6.716
- epoch: 2.0
- step: 2798

## 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: 3

### Framework versions

- Transformers 4.22.1
- Pytorch 1.12.1+cu102
- Datasets 2.9.0
- Tokenizers 0.12.1

# t5-small-finetuned-amazon-en-fr

This model is a fine-tuned version of t5-small on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.9766
- eval_rouge1: 0.1418
- eval_rouge2: 0.0716
- eval_rougeL: 0.1369
- eval_rougeLsum: 0.1383
- eval_runtime: 5.36
- eval_samples_per_second: 52.426
- eval_steps_per_second: 6.716
- epoch: 2.0
- step: 2798 ## 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: 3 ### Framework versions

- Transformers 4.22.1
- Pytorch 1.12.1+cu102
- Datasets 2.9.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # t5-small-finetuned-amazon-en-fr

This model is a fine-tuned version of t5-small on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.9766
- eval_rouge1: 0.1418
- eval_rouge2: 0.0716
- eval_rougeL: 0.1369
- eval_rougeLsum: 0.1383
- eval_runtime: 5.36
- eval_samples_per_second: 52.426
- eval_steps_per_second: 6.716
- epoch: 2.0
- step: 2798 ## 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: 3 ### Framework versions

- Transformers 4.22.1
- Pytorch 1.12.1+cu102
- Datasets 2.9.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# t5-small-finetuned-amazon-en-fr

This model is a fine-tuned version of t5-small on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.9766
- eval_rouge1: 0.1418
- eval_rouge2: 0.0716
- eval_rougeL: 0.1369
- eval_rougeLsum: 0.1383
- eval_runtime: 5.36
- eval_samples_per_second: 52.426
- eval_steps_per_second: 6.716
- epoch: 2.0
- step: 2798## 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: 3### Framework versions

- Transformers 4.22.1
- Pytorch 1.12.1+cu102
- Datasets 2.9.0
- Tokenizers 0.12.1