---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results_T5
  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. -->

# results_T5

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8755
- Rouge1: 0.2921
- Rouge2: 0.1519
- Rougel: 0.2857
- Rougelsum: 0.2866

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 1.0   | 109  | 0.4682          | 0.2349 | 0.0878 | 0.2327 | 0.2344    |
| No log        | 2.0   | 218  | 0.4153          | 0.2519 | 0.0965 | 0.2481 | 0.2503    |
| No log        | 3.0   | 327  | 0.4102          | 0.3011 | 0.1465 | 0.2979 | 0.2990    |
| No log        | 4.0   | 436  | 0.4386          | 0.2555 | 0.1138 | 0.2496 | 0.2496    |
| 0.8199        | 5.0   | 545  | 0.4784          | 0.2725 | 0.1188 | 0.2675 | 0.2665    |
| 0.8199        | 6.0   | 654  | 0.5088          | 0.2524 | 0.1066 | 0.2497 | 0.2501    |
| 0.8199        | 7.0   | 763  | 0.5680          | 0.2542 | 0.1093 | 0.2497 | 0.2496    |
| 0.8199        | 8.0   | 872  | 0.5982          | 0.2740 | 0.1375 | 0.2694 | 0.2698    |
| 0.8199        | 9.0   | 981  | 0.6575          | 0.2730 | 0.1368 | 0.2723 | 0.2714    |
| 0.0653        | 10.0  | 1090 | 0.6753          | 0.2822 | 0.1519 | 0.2798 | 0.2781    |
| 0.0653        | 11.0  | 1199 | 0.6923          | 0.2795 | 0.1486 | 0.2780 | 0.2774    |
| 0.0653        | 12.0  | 1308 | 0.7350          | 0.2471 | 0.1209 | 0.2458 | 0.2457    |
| 0.0653        | 13.0  | 1417 | 0.7698          | 0.2762 | 0.1463 | 0.2720 | 0.2733    |
| 0.0225        | 14.0  | 1526 | 0.7867          | 0.2771 | 0.1372 | 0.2763 | 0.2755    |
| 0.0225        | 15.0  | 1635 | 0.8166          | 0.3166 | 0.1689 | 0.3132 | 0.3133    |
| 0.0225        | 16.0  | 1744 | 0.8085          | 0.3027 | 0.1572 | 0.2998 | 0.3009    |
| 0.0225        | 17.0  | 1853 | 0.8162          | 0.3090 | 0.1734 | 0.3025 | 0.3038    |
| 0.0225        | 18.0  | 1962 | 0.8484          | 0.2965 | 0.1627 | 0.2917 | 0.2909    |
| 0.0105        | 19.0  | 2071 | 0.8610          | 0.2881 | 0.1487 | 0.2813 | 0.2819    |
| 0.0105        | 20.0  | 2180 | 0.8688          | 0.2811 | 0.1494 | 0.2755 | 0.2770    |
| 0.0105        | 21.0  | 2289 | 0.8733          | 0.2777 | 0.1453 | 0.2708 | 0.2724    |
| 0.0105        | 22.0  | 2398 | 0.8776          | 0.2771 | 0.1475 | 0.2709 | 0.2711    |
| 0.0061        | 23.0  | 2507 | 0.8717          | 0.2829 | 0.1467 | 0.2749 | 0.2749    |
| 0.0061        | 24.0  | 2616 | 0.8729          | 0.2878 | 0.1467 | 0.2803 | 0.2806    |
| 0.0061        | 25.0  | 2725 | 0.8755          | 0.2921 | 0.1519 | 0.2857 | 0.2866    |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3