--- license: mit base_model: facebook/bart-large-xsum tags: - generated_from_trainer datasets: - samsum metrics: - rouge model-index: - name: conversation-summ results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: samsum type: samsum config: samsum split: validation args: samsum metrics: - name: Rouge1 type: rouge value: 54.5208 --- # conversation-summ This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the samsum dataset. It achieves the following results on the evaluation set: - Loss: 0.3072 - Rouge1: 54.5208 - Rouge2: 29.613 - Rougel: 44.529 - Rougelsum: 49.9578 - Gen Len: 30.1968 ## 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: 2e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:---------:|:-------:| | 0.2898 | 1.0 | 3683 | 0.3072 | 54.5208 | 29.613 | 44.529 | 49.9578 | 30.1968 | ### Framework versions - Transformers 4.33.0 - Pytorch 2.0.0 - Datasets 2.1.0 - Tokenizers 0.13.3