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# bart-large-cnn

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.8506
- eval_rouge1: 0.3613
- eval_rouge2: 0.0744
- eval_rougeL: 0.1665
- eval_rougeLsum: 0.3401
- eval_gen_len: 385.8086
- eval_runtime: 8322.7751
- eval_samples_per_second: 0.151
- eval_steps_per_second: 0.076
- epoch: 0.99
- step: 63

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "model-index": [{"name": "bart-large-cnn", "results": []}]}
transformers pytorch tf jax tensorboard rust safetensors bart text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible region:us