---
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