---
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
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# 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