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# bart-cnn-samsum-finetuned

This model is a fine-tuned version of [dayaburamshetty/bart-cnn-samsum-finetuned](https://huggingface.co/dayaburamshetty/bart-cnn-samsum-finetuned) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1341

## 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-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1191        | 1.0   | 74   | 0.1344          |
| 0.0974        | 2.0   | 148  | 0.1341          |
| 0.1043        | 3.0   | 222  | 0.1342          |
| 0.0875        | 4.0   | 296  | 0.1341          |
| 0.0767        | 5.0   | 370  | 0.1341          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["samsum"], "base_model": "dayaburamshetty/bart-cnn-samsum-finetuned", "model-index": [{"name": "bart-cnn-samsum-finetuned", "results": []}]}
transformers tensorboard safetensors bart text2text-generation generated_from_trainer dataset:samsum base_model:dayaburamshetty/bart-cnn-samsum-finetuned license:mit autotrain_compatible endpoints_compatible region:us