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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-bart-20-epochs-wang-lab
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. -->
# fine-tuned-bart-20-epochs-wang-lab
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1462
- Rouge1: 0.2876
- Rouge2: 0.1104
- Rougel: 0.2587
- Rougelsum: 0.2583
- Gen Len: 15.32
## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 301 | 0.8236 | 0.2393 | 0.0872 | 0.2103 | 0.2098 | 15.1 |
| 2.6644 | 2.0 | 602 | 0.7800 | 0.2486 | 0.0882 | 0.219 | 0.2187 | 14.24 |
| 2.6644 | 3.0 | 903 | 0.7623 | 0.3152 | 0.131 | 0.2914 | 0.2901 | 15.83 |
| 0.6713 | 4.0 | 1204 | 0.7802 | 0.2909 | 0.104 | 0.2577 | 0.2577 | 14.4 |
| 0.4641 | 5.0 | 1505 | 0.8159 | 0.2986 | 0.1058 | 0.2629 | 0.2606 | 14.71 |
| 0.4641 | 6.0 | 1806 | 0.8451 | 0.3212 | 0.1374 | 0.2892 | 0.2892 | 15.3 |
| 0.2986 | 7.0 | 2107 | 0.8913 | 0.2965 | 0.115 | 0.2724 | 0.2728 | 15.25 |
| 0.2986 | 8.0 | 2408 | 0.9194 | 0.2686 | 0.1036 | 0.2395 | 0.2389 | 15.07 |
| 0.2025 | 9.0 | 2709 | 0.9674 | 0.283 | 0.1077 | 0.2549 | 0.2535 | 15.38 |
| 0.1397 | 10.0 | 3010 | 0.9848 | 0.2805 | 0.1127 | 0.2484 | 0.2475 | 15.99 |
| 0.1397 | 11.0 | 3311 | 1.0356 | 0.2943 | 0.1158 | 0.2568 | 0.2586 | 15.32 |
| 0.0922 | 12.0 | 3612 | 1.0481 | 0.3291 | 0.1211 | 0.297 | 0.2999 | 15.39 |
| 0.0922 | 13.0 | 3913 | 1.0846 | 0.2861 | 0.1074 | 0.2473 | 0.2482 | 15.04 |
| 0.0618 | 14.0 | 4214 | 1.0941 | 0.2929 | 0.103 | 0.2511 | 0.2505 | 15.34 |
| 0.042 | 15.0 | 4515 | 1.1076 | 0.2639 | 0.1111 | 0.2349 | 0.2328 | 15.11 |
| 0.042 | 16.0 | 4816 | 1.1180 | 0.2825 | 0.1125 | 0.2465 | 0.2452 | 15.08 |
| 0.03 | 17.0 | 5117 | 1.1310 | 0.2924 | 0.1073 | 0.2527 | 0.2528 | 15.47 |
| 0.03 | 18.0 | 5418 | 1.1407 | 0.2823 | 0.1017 | 0.2491 | 0.2471 | 15.1 |
| 0.0204 | 19.0 | 5719 | 1.1445 | 0.2952 | 0.1142 | 0.2635 | 0.264 | 15.13 |
| 0.0153 | 20.0 | 6020 | 1.1462 | 0.2876 | 0.1104 | 0.2587 | 0.2583 | 15.32 |
### Framework versions
- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0
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