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---
license: apache-2.0
base_model: Falconsai/text_summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: text_summarization-finetuned-stocknews_1900_100
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. -->
# text_summarization-finetuned-stocknews_1900_100
This model is a fine-tuned version of [Falconsai/text_summarization](https://huggingface.co/Falconsai/text_summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6071
- Rouge1: 15.4764
- Rouge2: 7.3425
- Rougel: 13.0298
- Rougelsum: 14.3613
- Gen Len: 19.0
## 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: 40
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| No log | 1.0 | 102 | 1.5996 | 15.7162 | 7.3225 | 13.1679 | 14.5316 | 19.0 |
| No log | 2.0 | 204 | 1.5991 | 15.7364 | 7.3916 | 13.2205 | 14.5865 | 19.0 |
| No log | 3.0 | 306 | 1.5948 | 15.7337 | 7.4936 | 13.2031 | 14.5941 | 19.0 |
| No log | 4.0 | 408 | 1.5935 | 15.7661 | 7.4892 | 13.1138 | 14.5123 | 19.0 |
| 1.4093 | 5.0 | 510 | 1.5972 | 15.6328 | 7.2837 | 13.1138 | 14.4789 | 19.0 |
| 1.4093 | 6.0 | 612 | 1.6016 | 15.5382 | 7.3117 | 13.0203 | 14.3907 | 19.0 |
| 1.4093 | 7.0 | 714 | 1.5983 | 15.5582 | 7.2532 | 12.9421 | 14.3971 | 19.0 |
| 1.4093 | 8.0 | 816 | 1.6039 | 15.5287 | 7.3152 | 13.002 | 14.3652 | 19.0 |
| 1.4093 | 9.0 | 918 | 1.6016 | 15.5916 | 7.3367 | 13.0811 | 14.442 | 19.0 |
| 1.3525 | 10.0 | 1020 | 1.6017 | 15.749 | 7.6355 | 13.1754 | 14.6339 | 19.0 |
| 1.3525 | 11.0 | 1122 | 1.5992 | 15.6529 | 7.5216 | 13.1041 | 14.5668 | 19.0 |
| 1.3525 | 12.0 | 1224 | 1.5977 | 15.64 | 7.3843 | 13.0609 | 14.5366 | 19.0 |
| 1.3525 | 13.0 | 1326 | 1.5993 | 15.6516 | 7.4595 | 13.1143 | 14.5799 | 19.0 |
| 1.3525 | 14.0 | 1428 | 1.6040 | 15.6532 | 7.5787 | 13.0764 | 14.5464 | 19.0 |
| 1.3156 | 15.0 | 1530 | 1.5998 | 15.4999 | 7.349 | 13.016 | 14.4233 | 19.0 |
| 1.3156 | 16.0 | 1632 | 1.6039 | 15.4718 | 7.2392 | 12.9167 | 14.3196 | 19.0 |
| 1.3156 | 17.0 | 1734 | 1.6026 | 15.5434 | 7.376 | 12.9885 | 14.3673 | 19.0 |
| 1.3156 | 18.0 | 1836 | 1.6008 | 15.4092 | 7.2119 | 12.9495 | 14.286 | 19.0 |
| 1.3156 | 19.0 | 1938 | 1.6009 | 15.4604 | 7.4049 | 13.0264 | 14.3634 | 19.0 |
| 1.2849 | 20.0 | 2040 | 1.6028 | 15.4735 | 7.3749 | 12.9979 | 14.3637 | 19.0 |
| 1.2849 | 21.0 | 2142 | 1.6025 | 15.617 | 7.5495 | 13.0912 | 14.4945 | 19.0 |
| 1.2849 | 22.0 | 2244 | 1.6061 | 15.65 | 7.6043 | 13.119 | 14.5419 | 19.0 |
| 1.2849 | 23.0 | 2346 | 1.6039 | 15.5747 | 7.5283 | 13.0601 | 14.4706 | 19.0 |
| 1.2849 | 24.0 | 2448 | 1.6071 | 15.4923 | 7.4246 | 12.9747 | 14.3495 | 19.0 |
| 1.2625 | 25.0 | 2550 | 1.6030 | 15.5403 | 7.4373 | 13.1005 | 14.4791 | 19.0 |
| 1.2625 | 26.0 | 2652 | 1.6044 | 15.5232 | 7.4625 | 13.049 | 14.4455 | 19.0 |
| 1.2625 | 27.0 | 2754 | 1.6038 | 15.4961 | 7.4241 | 13.0409 | 14.4496 | 19.0 |
| 1.2625 | 28.0 | 2856 | 1.6048 | 15.5079 | 7.551 | 13.0814 | 14.4369 | 19.0 |
| 1.2625 | 29.0 | 2958 | 1.6067 | 15.4629 | 7.4087 | 13.0123 | 14.3897 | 19.0 |
| 1.2418 | 30.0 | 3060 | 1.6052 | 15.5104 | 7.518 | 13.0891 | 14.4284 | 19.0 |
| 1.2418 | 31.0 | 3162 | 1.6051 | 15.5104 | 7.4773 | 13.0686 | 14.4114 | 19.0 |
| 1.2418 | 32.0 | 3264 | 1.6044 | 15.5491 | 7.5342 | 13.1145 | 14.4742 | 19.0 |
| 1.2418 | 33.0 | 3366 | 1.6064 | 15.5321 | 7.4773 | 13.0686 | 14.4336 | 19.0 |
| 1.2418 | 34.0 | 3468 | 1.6055 | 15.5193 | 7.5178 | 13.0887 | 14.4521 | 19.0 |
| 1.2313 | 35.0 | 3570 | 1.6057 | 15.4739 | 7.4526 | 13.0326 | 14.3947 | 19.0 |
| 1.2313 | 36.0 | 3672 | 1.6057 | 15.4486 | 7.3244 | 12.9881 | 14.3346 | 19.0 |
| 1.2313 | 37.0 | 3774 | 1.6067 | 15.4764 | 7.3795 | 13.0402 | 14.3886 | 19.0 |
| 1.2313 | 38.0 | 3876 | 1.6072 | 15.4594 | 7.3028 | 12.9813 | 14.3339 | 19.0 |
| 1.2313 | 39.0 | 3978 | 1.6070 | 15.4764 | 7.3795 | 13.0402 | 14.3886 | 19.0 |
| 1.2274 | 40.0 | 4080 | 1.6071 | 15.4764 | 7.3425 | 13.0298 | 14.3613 | 19.0 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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