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---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-samsum-icsi-ami-v2
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-icsi-ami-v2
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: 5.8987
- Rouge1: 39.0928
- Rouge2: 10.8408
- Rougel: 21.9138
- Rougelsum: 35.5067
- Gen Len: 138.7941
## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| No log | 1.0 | 135 | 3.2308 | 38.4274 | 13.6461 | 22.366 | 35.2353 | 185.7941 |
| No log | 2.0 | 270 | 3.3026 | 40.1748 | 11.7944 | 23.2655 | 36.4718 | 146.8529 |
| No log | 3.0 | 405 | 3.5199 | 39.8209 | 12.1621 | 22.7772 | 36.4967 | 141.7647 |
| 2.2131 | 4.0 | 540 | 4.0508 | 40.4325 | 11.6547 | 22.9958 | 36.8782 | 131.4412 |
| 2.2131 | 5.0 | 675 | 4.6988 | 38.4097 | 9.8309 | 20.3894 | 34.1967 | 145.9706 |
| 2.2131 | 6.0 | 810 | 4.9590 | 38.5758 | 9.6335 | 20.865 | 35.0321 | 169.2353 |
| 2.2131 | 7.0 | 945 | 5.4264 | 38.2813 | 9.5764 | 21.1406 | 34.5989 | 148.0294 |
| 0.401 | 8.0 | 1080 | 5.4887 | 38.3014 | 9.6881 | 21.2398 | 34.1584 | 139.3529 |
| 0.401 | 9.0 | 1215 | 5.8044 | 39.9603 | 10.4329 | 22.6895 | 36.2406 | 145.2353 |
| 0.401 | 10.0 | 1350 | 5.8987 | 39.0928 | 10.8408 | 21.9138 | 35.5067 | 138.7941 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
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