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# results

This model is a fine-tuned version of [sshleifer/distilbart-xsum-12-3](https://huggingface.co/sshleifer/distilbart-xsum-12-3) 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.
It achieves the following results on the evaluation set:
- eval_loss: 3.0155
- eval_rouge1: 46.2466
- eval_rouge2: 21.7289
- eval_rougeL: 38.0362
- eval_rougeLsum: 41.8935
- eval_gen_len: 25.8284
- eval_runtime: 554.679
- eval_samples_per_second: 5.609
- eval_steps_per_second: 1.403
- epoch: 0.33
- step: 2317

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- label_smoothing_factor: 0.1

### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "results", "results": []}]}
transformers pytorch bart text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 




# results

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on the knkarthick/AMI, knkarthick/dialogsum, and samsum datasets.
It achieves the following results on the evaluation set:
- eval_loss: 3.0155
- eval_rouge1: 46.2466
- eval_rouge2: 21.7289
- eval_rougeL: 38.0362
- eval_rougeLsum: 41.8935
- eval_gen_len: 25.8284
- eval_runtime: 554.679
- eval_samples_per_second: 5.609
- eval_steps_per_second: 1.403
- epoch: 0.33
- step: 2317

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- label_smoothing_factor: 0.1

### 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 sshleifer/distilbart-xsum-12-3 on the knkarthick/AMI, knkarthick/dialogsum, and samsum datasets.
It achieves the following results on the evaluation set:
- eval_loss: 3.0155
- eval_rouge1: 46.2466
- eval_rouge2: 21.7289
- eval_rougeL: 38.0362
- eval_rougeLsum: 41.8935
- eval_gen_len: 25.8284
- eval_runtime: 554.679
- eval_samples_per_second: 5.609
- eval_steps_per_second: 1.403
- epoch: 0.33
- step: 2317 ## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- label_smoothing_factor: 0.1 ### Framework versions

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

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on the knkarthick/AMI, knkarthick/dialogsum, and samsum datasets.
It achieves the following results on the evaluation set:
- eval_loss: 3.0155
- eval_rouge1: 46.2466
- eval_rouge2: 21.7289
- eval_rougeL: 38.0362
- eval_rougeLsum: 41.8935
- eval_gen_len: 25.8284
- eval_runtime: 554.679
- eval_samples_per_second: 5.609
- eval_steps_per_second: 1.403
- epoch: 0.33
- step: 2317 ## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- label_smoothing_factor: 0.1 ### Framework versions

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

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on the knkarthick/AMI, knkarthick/dialogsum, and samsum datasets.
It achieves the following results on the evaluation set:
- eval_loss: 3.0155
- eval_rouge1: 46.2466
- eval_rouge2: 21.7289
- eval_rougeL: 38.0362
- eval_rougeLsum: 41.8935
- eval_gen_len: 25.8284
- eval_runtime: 554.679
- eval_samples_per_second: 5.609
- eval_steps_per_second: 1.403
- epoch: 0.33
- step: 2317## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- label_smoothing_factor: 0.1### Framework versions

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