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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
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
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: 0.8098
- Rouge1: 0.3246
- Rouge2: 0.1287
- Rougel: 0.2921
- Rougelsum: 0.2912
- Gen Len: 14.96
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 301 | 0.7895 | 0.2498 | 0.0834 | 0.2162 | 0.2159 | 14.58 |
| 1.8122 | 2.0 | 602 | 0.7331 | 0.2226 | 0.0794 | 0.1943 | 0.1931 | 13.51 |
| 1.8122 | 3.0 | 903 | 0.7235 | 0.2935 | 0.1013 | 0.2652 | 0.2647 | 14.69 |
| 0.6848 | 4.0 | 1204 | 0.7225 | 0.322 | 0.1245 | 0.2867 | 0.2857 | 13.92 |
| 0.5826 | 5.0 | 1505 | 0.7238 | 0.322 | 0.1149 | 0.2863 | 0.2854 | 14.81 |
| 0.5826 | 6.0 | 1806 | 0.7204 | 0.3255 | 0.1212 | 0.2977 | 0.2963 | 14.98 |
| 0.5013 | 7.0 | 2107 | 0.7377 | 0.3061 | 0.1104 | 0.2784 | 0.2767 | 14.84 |
| 0.5013 | 8.0 | 2408 | 0.7396 | 0.3092 | 0.1227 | 0.275 | 0.2741 | 14.17 |
| 0.4384 | 9.0 | 2709 | 0.7413 | 0.3224 | 0.1271 | 0.2935 | 0.2928 | 14.44 |
| 0.3952 | 10.0 | 3010 | 0.7458 | 0.3288 | 0.1302 | 0.2925 | 0.2925 | 15.09 |
| 0.3952 | 11.0 | 3311 | 0.7615 | 0.3496 | 0.139 | 0.3139 | 0.3137 | 15.13 |
| 0.3626 | 12.0 | 3612 | 0.7733 | 0.3311 | 0.1264 | 0.3057 | 0.3049 | 14.84 |
| 0.3626 | 13.0 | 3913 | 0.7779 | 0.3184 | 0.1226 | 0.286 | 0.2857 | 15.02 |
| 0.3254 | 14.0 | 4214 | 0.7854 | 0.3258 | 0.1199 | 0.2911 | 0.2915 | 14.89 |
| 0.2983 | 15.0 | 4515 | 0.7863 | 0.3346 | 0.1189 | 0.3027 | 0.3009 | 14.93 |
| 0.2983 | 16.0 | 4816 | 0.7979 | 0.3201 | 0.117 | 0.2857 | 0.2843 | 15.05 |
| 0.2807 | 17.0 | 5117 | 0.8037 | 0.3223 | 0.1216 | 0.291 | 0.2899 | 15.1 |
| 0.2807 | 18.0 | 5418 | 0.8048 | 0.3313 | 0.1261 | 0.3003 | 0.2996 | 15.1 |
| 0.2653 | 19.0 | 5719 | 0.8114 | 0.3285 | 0.1298 | 0.297 | 0.2963 | 15.01 |
| 0.2562 | 20.0 | 6020 | 0.8098 | 0.3246 | 0.1287 | 0.2921 | 0.2912 | 14.96 |
### Framework versions
- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0
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