| Quantization made by Richard Erkhov. | |
| [Github](https://github.com/RichardErkhov) | |
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| bart-base-finetuned-xsum - bnb 4bits | |
| - Model creator: https://huggingface.co/Vexemous/ | |
| - Original model: https://huggingface.co/Vexemous/bart-base-finetuned-xsum/ | |
| Original model description: | |
| --- | |
| license: apache-2.0 | |
| base_model: facebook/bart-base | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - xsum | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: bart-base-finetuned-xsum | |
| results: | |
| - task: | |
| name: Sequence-to-sequence Language Modeling | |
| type: text2text-generation | |
| dataset: | |
| name: xsum | |
| type: xsum | |
| config: default | |
| split: train[:10%] | |
| args: default | |
| metrics: | |
| - name: Rouge1 | |
| type: rouge | |
| value: 35.8214 | |
| pipeline_tag: summarization | |
| --- | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # bart-base-finetuned-xsum | |
| This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the xsum dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.9356 | |
| - Rouge1: 35.8214 | |
| - Rouge2: 14.7565 | |
| - Rougel: 29.4566 | |
| - Rougelsum: 29.4496 | |
| - Gen Len: 19.562 | |
| ## 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: 16 | |
| - eval_batch_size: 16 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 5 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | |
| | 2.301 | 1.0 | 1148 | 1.9684 | 34.4715 | 13.6638 | 28.1147 | 28.1204 | 19.5816 | | |
| | 2.1197 | 2.0 | 2296 | 1.9442 | 35.2502 | 14.284 | 28.8462 | 28.8384 | 19.5546 | | |
| | 1.9804 | 3.0 | 3444 | 1.9406 | 35.7799 | 14.7422 | 29.3669 | 29.3742 | 19.5326 | | |
| | 1.8891 | 4.0 | 4592 | 1.9349 | 35.5151 | 14.4668 | 29.0359 | 29.0484 | 19.5492 | | |
| | 1.827 | 5.0 | 5740 | 1.9356 | 35.8214 | 14.7565 | 29.4566 | 29.4496 | 19.562 | | |
| ### Framework versions | |
| - Transformers 4.40.1 | |
| - Pytorch 1.13.1+cu117 | |
| - Datasets 2.19.0 | |
| - Tokenizers 0.19.1 | |