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---
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-finetuned-stocknews_1
  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. -->

# t5-base-finetuned-stocknews_1

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4299
- Rouge1: 31.2675
- Rouge2: 18.3987
- Rougel: 27.1272
- Rougelsum: 28.0372
- 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 99   | 1.1909          | 26.7564 | 14.0847 | 23.0574 | 24.0225   | 19.0    |
| No log        | 2.0   | 198  | 1.1513          | 26.8525 | 14.3487 | 23.0252 | 24.0357   | 19.0    |
| No log        | 3.0   | 297  | 1.1358          | 27.9251 | 15.4858 | 24.1529 | 25.0564   | 19.0    |
| No log        | 4.0   | 396  | 1.1249          | 28.9647 | 16.322  | 25.1393 | 25.9351   | 19.0    |
| No log        | 5.0   | 495  | 1.1230          | 29.3277 | 16.643  | 25.3965 | 26.3924   | 19.0    |
| 1.1304        | 6.0   | 594  | 1.1257          | 29.3298 | 16.6756 | 25.2931 | 26.3113   | 19.0    |
| 1.1304        | 7.0   | 693  | 1.1274          | 29.8143 | 17.0961 | 25.8392 | 26.7922   | 19.0    |
| 1.1304        | 8.0   | 792  | 1.1349          | 29.7039 | 16.8019 | 25.7436 | 26.7177   | 19.0    |
| 1.1304        | 9.0   | 891  | 1.1398          | 29.7954 | 17.0393 | 25.9506 | 26.6055   | 19.0    |
| 1.1304        | 10.0  | 990  | 1.1436          | 30.2308 | 17.5247 | 26.6431 | 27.2773   | 19.0    |
| 0.8223        | 11.0  | 1089 | 1.1646          | 30.1807 | 17.4666 | 26.4978 | 27.1534   | 19.0    |
| 0.8223        | 12.0  | 1188 | 1.1700          | 30.1808 | 17.7926 | 26.5241 | 27.2625   | 19.0    |
| 0.8223        | 13.0  | 1287 | 1.1811          | 30.5494 | 18.0376 | 26.7185 | 27.5291   | 19.0    |
| 0.8223        | 14.0  | 1386 | 1.1847          | 30.4785 | 18.0418 | 26.8702 | 27.5021   | 19.0    |
| 0.8223        | 15.0  | 1485 | 1.2043          | 30.5933 | 18.3907 | 27.1218 | 27.8091   | 19.0    |
| 0.6312        | 16.0  | 1584 | 1.2219          | 30.5586 | 18.5247 | 26.8513 | 27.6566   | 19.0    |
| 0.6312        | 17.0  | 1683 | 1.2214          | 30.5018 | 18.1947 | 26.9409 | 27.7452   | 19.0    |
| 0.6312        | 18.0  | 1782 | 1.2322          | 30.6322 | 18.1167 | 26.6699 | 27.509    | 19.0    |
| 0.6312        | 19.0  | 1881 | 1.2421          | 31.0753 | 18.5194 | 27.0614 | 27.912    | 19.0    |
| 0.6312        | 20.0  | 1980 | 1.2566          | 30.8549 | 18.3715 | 27.0343 | 27.8685   | 19.0    |
| 0.513         | 21.0  | 2079 | 1.2740          | 30.7621 | 18.5321 | 26.9539 | 27.7937   | 19.0    |
| 0.513         | 22.0  | 2178 | 1.2798          | 31.6185 | 18.7955 | 27.4786 | 28.2485   | 19.0    |
| 0.513         | 23.0  | 2277 | 1.2859          | 31.0127 | 18.438  | 27.0895 | 27.833    | 19.0    |
| 0.513         | 24.0  | 2376 | 1.3103          | 31.4955 | 18.4432 | 27.3754 | 28.1693   | 19.0    |
| 0.513         | 25.0  | 2475 | 1.3260          | 31.6346 | 18.3461 | 27.2447 | 28.1406   | 19.0    |
| 0.4278        | 26.0  | 2574 | 1.3191          | 31.6779 | 18.5516 | 27.5072 | 28.3363   | 19.0    |
| 0.4278        | 27.0  | 2673 | 1.3293          | 31.2316 | 18.2088 | 27.0875 | 27.9376   | 19.0    |
| 0.4278        | 28.0  | 2772 | 1.3313          | 31.2469 | 18.3832 | 27.2194 | 27.9704   | 19.0    |
| 0.4278        | 29.0  | 2871 | 1.3440          | 31.6021 | 18.5638 | 27.328  | 28.2197   | 19.0    |
| 0.4278        | 30.0  | 2970 | 1.3473          | 31.7773 | 18.5585 | 27.5498 | 28.3816   | 19.0    |
| 0.3693        | 31.0  | 3069 | 1.3598          | 31.2278 | 18.5905 | 27.0409 | 27.8962   | 19.0    |
| 0.3693        | 32.0  | 3168 | 1.3686          | 31.0198 | 18.4271 | 26.8683 | 27.9364   | 19.0    |
| 0.3693        | 33.0  | 3267 | 1.3798          | 30.8732 | 18.5114 | 26.9202 | 27.8493   | 19.0    |
| 0.3693        | 34.0  | 3366 | 1.3805          | 31.2322 | 18.7093 | 27.3125 | 28.1878   | 19.0    |
| 0.3693        | 35.0  | 3465 | 1.3870          | 31.0199 | 18.5469 | 27.1357 | 27.9645   | 19.0    |
| 0.3289        | 36.0  | 3564 | 1.3916          | 31.3317 | 18.7421 | 27.3709 | 28.2084   | 19.0    |
| 0.3289        | 37.0  | 3663 | 1.3961          | 31.2699 | 18.7424 | 27.3036 | 28.1781   | 19.0    |
| 0.3289        | 38.0  | 3762 | 1.4041          | 31.0176 | 18.4756 | 27.1868 | 27.9935   | 19.0    |
| 0.3289        | 39.0  | 3861 | 1.4104          | 31.1198 | 18.3739 | 27.1332 | 27.979    | 19.0    |
| 0.3289        | 40.0  | 3960 | 1.4142          | 30.9397 | 18.4267 | 27.1613 | 27.952    | 19.0    |
| 0.2963        | 41.0  | 4059 | 1.4191          | 31.2112 | 18.5405 | 27.2365 | 28.0131   | 19.0    |
| 0.2963        | 42.0  | 4158 | 1.4159          | 31.4348 | 18.6802 | 27.2705 | 28.1629   | 19.0    |
| 0.2963        | 43.0  | 4257 | 1.4217          | 31.3161 | 18.4061 | 27.1797 | 27.9911   | 19.0    |
| 0.2963        | 44.0  | 4356 | 1.4221          | 31.2979 | 18.6064 | 27.2486 | 28.1006   | 19.0    |
| 0.2963        | 45.0  | 4455 | 1.4231          | 31.24   | 18.4439 | 27.1825 | 28.0577   | 19.0    |
| 0.2796        | 46.0  | 4554 | 1.4251          | 31.24   | 18.4439 | 27.1825 | 28.0577   | 19.0    |
| 0.2796        | 47.0  | 4653 | 1.4278          | 31.3015 | 18.4439 | 27.213  | 28.1327   | 19.0    |
| 0.2796        | 48.0  | 4752 | 1.4292          | 31.2708 | 18.3724 | 27.1466 | 28.0132   | 19.0    |
| 0.2796        | 49.0  | 4851 | 1.4297          | 31.2675 | 18.3987 | 27.1272 | 28.0372   | 19.0    |
| 0.2796        | 50.0  | 4950 | 1.4299          | 31.2675 | 18.3987 | 27.1272 | 28.0372   | 19.0    |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2