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--- |
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license: apache-2.0 |
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base_model: google-t5/t5-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-base-finetuned-stocknews_1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# t5-base-finetuned-stocknews_1 |
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4299 |
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- Rouge1: 31.2675 |
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- Rouge2: 18.3987 |
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- Rougel: 27.1272 |
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- Rougelsum: 28.0372 |
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- Gen Len: 19.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| No log | 1.0 | 99 | 1.1909 | 26.7564 | 14.0847 | 23.0574 | 24.0225 | 19.0 | |
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| No log | 2.0 | 198 | 1.1513 | 26.8525 | 14.3487 | 23.0252 | 24.0357 | 19.0 | |
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| No log | 3.0 | 297 | 1.1358 | 27.9251 | 15.4858 | 24.1529 | 25.0564 | 19.0 | |
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| No log | 4.0 | 396 | 1.1249 | 28.9647 | 16.322 | 25.1393 | 25.9351 | 19.0 | |
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| No log | 5.0 | 495 | 1.1230 | 29.3277 | 16.643 | 25.3965 | 26.3924 | 19.0 | |
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| 1.1304 | 6.0 | 594 | 1.1257 | 29.3298 | 16.6756 | 25.2931 | 26.3113 | 19.0 | |
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| 1.1304 | 7.0 | 693 | 1.1274 | 29.8143 | 17.0961 | 25.8392 | 26.7922 | 19.0 | |
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| 1.1304 | 8.0 | 792 | 1.1349 | 29.7039 | 16.8019 | 25.7436 | 26.7177 | 19.0 | |
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| 1.1304 | 9.0 | 891 | 1.1398 | 29.7954 | 17.0393 | 25.9506 | 26.6055 | 19.0 | |
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| 1.1304 | 10.0 | 990 | 1.1436 | 30.2308 | 17.5247 | 26.6431 | 27.2773 | 19.0 | |
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| 0.8223 | 11.0 | 1089 | 1.1646 | 30.1807 | 17.4666 | 26.4978 | 27.1534 | 19.0 | |
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| 0.8223 | 12.0 | 1188 | 1.1700 | 30.1808 | 17.7926 | 26.5241 | 27.2625 | 19.0 | |
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| 0.8223 | 13.0 | 1287 | 1.1811 | 30.5494 | 18.0376 | 26.7185 | 27.5291 | 19.0 | |
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| 0.8223 | 14.0 | 1386 | 1.1847 | 30.4785 | 18.0418 | 26.8702 | 27.5021 | 19.0 | |
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| 0.8223 | 15.0 | 1485 | 1.2043 | 30.5933 | 18.3907 | 27.1218 | 27.8091 | 19.0 | |
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| 0.6312 | 16.0 | 1584 | 1.2219 | 30.5586 | 18.5247 | 26.8513 | 27.6566 | 19.0 | |
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| 0.6312 | 17.0 | 1683 | 1.2214 | 30.5018 | 18.1947 | 26.9409 | 27.7452 | 19.0 | |
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| 0.6312 | 18.0 | 1782 | 1.2322 | 30.6322 | 18.1167 | 26.6699 | 27.509 | 19.0 | |
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| 0.6312 | 19.0 | 1881 | 1.2421 | 31.0753 | 18.5194 | 27.0614 | 27.912 | 19.0 | |
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| 0.6312 | 20.0 | 1980 | 1.2566 | 30.8549 | 18.3715 | 27.0343 | 27.8685 | 19.0 | |
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| 0.513 | 21.0 | 2079 | 1.2740 | 30.7621 | 18.5321 | 26.9539 | 27.7937 | 19.0 | |
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| 0.513 | 22.0 | 2178 | 1.2798 | 31.6185 | 18.7955 | 27.4786 | 28.2485 | 19.0 | |
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| 0.513 | 23.0 | 2277 | 1.2859 | 31.0127 | 18.438 | 27.0895 | 27.833 | 19.0 | |
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| 0.513 | 24.0 | 2376 | 1.3103 | 31.4955 | 18.4432 | 27.3754 | 28.1693 | 19.0 | |
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| 0.513 | 25.0 | 2475 | 1.3260 | 31.6346 | 18.3461 | 27.2447 | 28.1406 | 19.0 | |
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| 0.4278 | 26.0 | 2574 | 1.3191 | 31.6779 | 18.5516 | 27.5072 | 28.3363 | 19.0 | |
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| 0.4278 | 27.0 | 2673 | 1.3293 | 31.2316 | 18.2088 | 27.0875 | 27.9376 | 19.0 | |
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| 0.4278 | 28.0 | 2772 | 1.3313 | 31.2469 | 18.3832 | 27.2194 | 27.9704 | 19.0 | |
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| 0.4278 | 29.0 | 2871 | 1.3440 | 31.6021 | 18.5638 | 27.328 | 28.2197 | 19.0 | |
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| 0.4278 | 30.0 | 2970 | 1.3473 | 31.7773 | 18.5585 | 27.5498 | 28.3816 | 19.0 | |
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| 0.3693 | 31.0 | 3069 | 1.3598 | 31.2278 | 18.5905 | 27.0409 | 27.8962 | 19.0 | |
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| 0.3693 | 32.0 | 3168 | 1.3686 | 31.0198 | 18.4271 | 26.8683 | 27.9364 | 19.0 | |
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| 0.3693 | 33.0 | 3267 | 1.3798 | 30.8732 | 18.5114 | 26.9202 | 27.8493 | 19.0 | |
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| 0.3693 | 34.0 | 3366 | 1.3805 | 31.2322 | 18.7093 | 27.3125 | 28.1878 | 19.0 | |
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| 0.3693 | 35.0 | 3465 | 1.3870 | 31.0199 | 18.5469 | 27.1357 | 27.9645 | 19.0 | |
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| 0.3289 | 36.0 | 3564 | 1.3916 | 31.3317 | 18.7421 | 27.3709 | 28.2084 | 19.0 | |
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| 0.3289 | 37.0 | 3663 | 1.3961 | 31.2699 | 18.7424 | 27.3036 | 28.1781 | 19.0 | |
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| 0.3289 | 38.0 | 3762 | 1.4041 | 31.0176 | 18.4756 | 27.1868 | 27.9935 | 19.0 | |
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| 0.3289 | 39.0 | 3861 | 1.4104 | 31.1198 | 18.3739 | 27.1332 | 27.979 | 19.0 | |
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| 0.3289 | 40.0 | 3960 | 1.4142 | 30.9397 | 18.4267 | 27.1613 | 27.952 | 19.0 | |
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| 0.2963 | 41.0 | 4059 | 1.4191 | 31.2112 | 18.5405 | 27.2365 | 28.0131 | 19.0 | |
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| 0.2963 | 42.0 | 4158 | 1.4159 | 31.4348 | 18.6802 | 27.2705 | 28.1629 | 19.0 | |
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| 0.2963 | 43.0 | 4257 | 1.4217 | 31.3161 | 18.4061 | 27.1797 | 27.9911 | 19.0 | |
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| 0.2963 | 44.0 | 4356 | 1.4221 | 31.2979 | 18.6064 | 27.2486 | 28.1006 | 19.0 | |
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| 0.2963 | 45.0 | 4455 | 1.4231 | 31.24 | 18.4439 | 27.1825 | 28.0577 | 19.0 | |
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| 0.2796 | 46.0 | 4554 | 1.4251 | 31.24 | 18.4439 | 27.1825 | 28.0577 | 19.0 | |
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| 0.2796 | 47.0 | 4653 | 1.4278 | 31.3015 | 18.4439 | 27.213 | 28.1327 | 19.0 | |
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| 0.2796 | 48.0 | 4752 | 1.4292 | 31.2708 | 18.3724 | 27.1466 | 28.0132 | 19.0 | |
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| 0.2796 | 49.0 | 4851 | 1.4297 | 31.2675 | 18.3987 | 27.1272 | 28.0372 | 19.0 | |
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| 0.2796 | 50.0 | 4950 | 1.4299 | 31.2675 | 18.3987 | 27.1272 | 28.0372 | 19.0 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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