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# models_and_tokenizers

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.4721
- eval_rouge1: 45.9566
- eval_rouge2: 22.0863
- eval_rougeL: 38.238
- eval_rougeLsum: 41.9378
- eval_get_len: 16.9096
- eval_runtime: 131.3434
- eval_samples_per_second: 6.236
- eval_steps_per_second: 0.784
- 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: 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: 1

### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2

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




# models_and_tokenizers

This model is a fine-tuned version of google/flan-t5-base on the samsum dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.4721
- eval_rouge1: 45.9566
- eval_rouge2: 22.0863
- eval_rougeL: 38.238
- eval_rougeLsum: 41.9378
- eval_get_len: 16.9096
- eval_runtime: 131.3434
- eval_samples_per_second: 6.236
- eval_steps_per_second: 0.784
- 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: 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: 1

### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2

# models_and_tokenizers

This model is a fine-tuned version of google/flan-t5-base on the samsum dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.4721
- eval_rouge1: 45.9566
- eval_rouge2: 22.0863
- eval_rougeL: 38.238
- eval_rougeLsum: 41.9378
- eval_get_len: 16.9096
- eval_runtime: 131.3434
- eval_samples_per_second: 6.236
- eval_steps_per_second: 0.784
- 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: 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: 1 ### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-samsum #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # models_and_tokenizers

This model is a fine-tuned version of google/flan-t5-base on the samsum dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.4721
- eval_rouge1: 45.9566
- eval_rouge2: 22.0863
- eval_rougeL: 38.238
- eval_rougeLsum: 41.9378
- eval_get_len: 16.9096
- eval_runtime: 131.3434
- eval_samples_per_second: 6.236
- eval_steps_per_second: 0.784
- 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: 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: 1 ### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-samsum #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# models_and_tokenizers

This model is a fine-tuned version of google/flan-t5-base on the samsum dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.4721
- eval_rouge1: 45.9566
- eval_rouge2: 22.0863
- eval_rougeL: 38.238
- eval_rougeLsum: 41.9378
- eval_get_len: 16.9096
- eval_runtime: 131.3434
- eval_samples_per_second: 6.236
- eval_steps_per_second: 0.784
- 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: 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: 1### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2