| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: bart-large-cnn-samsum-acsi-ami | |
| results: [] | |
| <!-- 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-large-cnn-samsum-acsi-ami | |
| This model is a fine-tuned version of [philschmid/bart-large-cnn-samsum](https://huggingface.co/philschmid/bart-large-cnn-samsum) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 3.1361 | |
| - Rouge1: 39.7563 | |
| - Rouge2: 11.1286 | |
| - Rougel: 23.2632 | |
| - Rougelsum: 36.5664 | |
| - Gen Len: 108.15 | |
| ## 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: 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | |
| | No log | 1.0 | 20 | 3.2095 | 39.8174 | 11.5559 | 24.0296 | 36.3048 | 108.5 | | |
| | No log | 2.0 | 40 | 3.1361 | 39.7563 | 11.1286 | 23.2632 | 36.5664 | 108.15 | | |
| | No log | 3.0 | 60 | 3.1599 | 41.79 | 12.0967 | 23.5336 | 37.6859 | 122.95 | | |
| | No log | 4.0 | 80 | 3.2878 | 42.3161 | 12.2801 | 23.9352 | 38.2391 | 122.7 | | |
| | No log | 5.0 | 100 | 3.3671 | 40.7968 | 10.7336 | 22.9434 | 36.4383 | 129.225 | | |
| ### Framework versions | |
| - Transformers 4.26.0 | |
| - Pytorch 1.13.1 | |
| - Datasets 2.9.0 | |
| - Tokenizers 0.13.2 | |