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# results

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the [knkarthick/AMI](https://huggingface.co/datasets/knkarthick/AMI), [knkarthick/dialogsum](https://huggingface.co/datasets/knkarthick/dialogsum), and [samsum](https://huggingface.co/datasets/samsum) datasets.

## 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: 1e-4
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- summary_len: 150
- max_len: 512
- num_epochs: <1

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
{"license": "apache-2.0", "model-index": [{"name": "results", "results": []}]}
transformers pytorch t5 text2text-generation license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# results

This model is a fine-tuned version of t5-base on the knkarthick/AMI, knkarthick/dialogsum, and samsum datasets.

## 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: 1e-4
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- summary_len: 150
- max_len: 512
- num_epochs: <1

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
# results

This model is a fine-tuned version of t5-base on the knkarthick/AMI, knkarthick/dialogsum, and samsum datasets. ## 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: 1e-4
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- summary_len: 150
- max_len: 512
- num_epochs: <1 ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #t5 #text2text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # results

This model is a fine-tuned version of t5-base on the knkarthick/AMI, knkarthick/dialogsum, and samsum datasets. ## 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: 1e-4
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- summary_len: 150
- max_len: 512
- num_epochs: <1 ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #t5 #text2text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# results

This model is a fine-tuned version of t5-base on the knkarthick/AMI, knkarthick/dialogsum, and samsum datasets.## 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: 1e-4
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- summary_len: 150
- max_len: 512
- num_epochs: <1### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3