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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_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. -->
# t5-base-finetuned-stocknews_1900_100
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: 1.2997
- Rouge1: 16.6203
- Rouge2: 8.7831
- Rougel: 13.9116
- Rougelsum: 15.4831
- 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 | 1.5488 | 14.6381 | 6.8963 | 12.1802 | 13.6527 | 19.0 |
| No log | 2.0 | 204 | 1.4139 | 15.0451 | 6.9216 | 12.6068 | 14.1445 | 19.0 |
| No log | 3.0 | 306 | 1.3627 | 15.3864 | 7.115 | 12.6537 | 14.267 | 19.0 |
| No log | 4.0 | 408 | 1.3288 | 15.6891 | 7.5106 | 13.0451 | 14.6203 | 19.0 |
| 1.8685 | 5.0 | 510 | 1.3087 | 15.8071 | 7.6382 | 13.103 | 14.7587 | 19.0 |
| 1.8685 | 6.0 | 612 | 1.2938 | 15.6775 | 7.6448 | 13.0823 | 14.6034 | 19.0 |
| 1.8685 | 7.0 | 714 | 1.2870 | 15.7672 | 7.89 | 13.3325 | 14.7821 | 19.0 |
| 1.8685 | 8.0 | 816 | 1.2779 | 16.1616 | 8.1642 | 13.4471 | 15.0305 | 19.0 |
| 1.8685 | 9.0 | 918 | 1.2731 | 16.3679 | 8.4804 | 13.7618 | 15.3468 | 19.0 |
| 1.1991 | 10.0 | 1020 | 1.2695 | 16.2821 | 8.456 | 13.7692 | 15.2461 | 19.0 |
| 1.1991 | 11.0 | 1122 | 1.2647 | 16.4056 | 8.5019 | 13.7217 | 15.3711 | 19.0 |
| 1.1991 | 12.0 | 1224 | 1.2667 | 16.4259 | 8.6692 | 13.8396 | 15.4122 | 19.0 |
| 1.1991 | 13.0 | 1326 | 1.2654 | 16.6988 | 8.9574 | 14.0239 | 15.6864 | 19.0 |
| 1.1991 | 14.0 | 1428 | 1.2648 | 16.7394 | 9.0588 | 14.0529 | 15.6644 | 19.0 |
| 1.0382 | 15.0 | 1530 | 1.2642 | 16.6864 | 9.106 | 13.9046 | 15.5687 | 19.0 |
| 1.0382 | 16.0 | 1632 | 1.2662 | 16.6786 | 8.8288 | 13.9603 | 15.5724 | 19.0 |
| 1.0382 | 17.0 | 1734 | 1.2651 | 16.7446 | 8.9211 | 13.9999 | 15.6617 | 19.0 |
| 1.0382 | 18.0 | 1836 | 1.2702 | 16.6361 | 8.8503 | 14.0324 | 15.546 | 19.0 |
| 1.0382 | 19.0 | 1938 | 1.2676 | 16.7046 | 9.0089 | 14.073 | 15.6342 | 19.0 |
| 0.9273 | 20.0 | 2040 | 1.2732 | 16.4339 | 8.6714 | 13.8422 | 15.44 | 19.0 |
| 0.9273 | 21.0 | 2142 | 1.2743 | 16.5655 | 8.7747 | 13.839 | 15.4958 | 19.0 |
| 0.9273 | 22.0 | 2244 | 1.2781 | 16.7749 | 8.9154 | 14.1216 | 15.6395 | 19.0 |
| 0.9273 | 23.0 | 2346 | 1.2814 | 16.535 | 8.7436 | 13.971 | 15.5056 | 19.0 |
| 0.9273 | 24.0 | 2448 | 1.2795 | 16.6612 | 8.7045 | 14.0096 | 15.5692 | 19.0 |
| 0.8539 | 25.0 | 2550 | 1.2844 | 16.6083 | 8.6106 | 13.9202 | 15.5641 | 19.0 |
| 0.8539 | 26.0 | 2652 | 1.2817 | 16.6449 | 8.8127 | 14.0562 | 15.5792 | 19.0 |
| 0.8539 | 27.0 | 2754 | 1.2856 | 16.6185 | 8.7475 | 14.0134 | 15.5439 | 19.0 |
| 0.8539 | 28.0 | 2856 | 1.2868 | 16.4913 | 8.7293 | 13.9367 | 15.4702 | 19.0 |
| 0.8539 | 29.0 | 2958 | 1.2905 | 16.4887 | 8.6461 | 13.8893 | 15.4342 | 19.0 |
| 0.8006 | 30.0 | 3060 | 1.2893 | 16.5861 | 8.695 | 13.9081 | 15.4307 | 19.0 |
| 0.8006 | 31.0 | 3162 | 1.2919 | 16.5972 | 8.8314 | 13.9069 | 15.4967 | 19.0 |
| 0.8006 | 32.0 | 3264 | 1.2940 | 16.5957 | 8.789 | 13.9202 | 15.4839 | 19.0 |
| 0.8006 | 33.0 | 3366 | 1.2946 | 16.6313 | 8.8011 | 13.9684 | 15.5256 | 19.0 |
| 0.8006 | 34.0 | 3468 | 1.2945 | 16.6711 | 8.8915 | 14.0228 | 15.5394 | 19.0 |
| 0.7598 | 35.0 | 3570 | 1.2970 | 16.67 | 8.891 | 13.9749 | 15.5174 | 19.0 |
| 0.7598 | 36.0 | 3672 | 1.2975 | 16.6223 | 8.7522 | 13.9528 | 15.4761 | 19.0 |
| 0.7598 | 37.0 | 3774 | 1.2987 | 16.6444 | 8.8594 | 13.9567 | 15.5117 | 19.0 |
| 0.7598 | 38.0 | 3876 | 1.2993 | 16.6444 | 8.8594 | 13.9567 | 15.5117 | 19.0 |
| 0.7598 | 39.0 | 3978 | 1.2996 | 16.6196 | 8.8108 | 13.9213 | 15.4806 | 19.0 |
| 0.7463 | 40.0 | 4080 | 1.2997 | 16.6203 | 8.7831 | 13.9116 | 15.4831 | 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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