---
license: apache-2.0
base_model: Hasanur525/deed_summarization_mt5_version_1
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-deed-sum
  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. -->

# mt5-deed-sum

This model is a fine-tuned version of [Hasanur525/deed_summarization_mt5_version_1](https://huggingface.co/Hasanur525/deed_summarization_mt5_version_1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4953
- Rouge1: 1.5754
- Rouge2: 1.087
- Rougel: 1.5005
- Rougelsum: 1.4211
- Gen Len: 310.6981

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 22

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 0.0915        | 1.0   | 375  | 0.5844          | 0.7311 | 0.4193 | 0.7311 | 0.7311    | 289.3396 |
| 0.9545        | 2.0   | 750  | 0.5858          | 0.6289 | 0.444  | 0.6289 | 0.6289    | 291.5912 |
| 0.8026        | 3.0   | 1125 | 0.5817          | 1.1119 | 0.6733 | 1.067  | 1.0428    | 295.0692 |
| 0.2525        | 4.0   | 1500 | 0.5698          | 0.7311 | 0.4193 | 0.7311 | 0.7311    | 299.7987 |
| 1.5794        | 5.0   | 1875 | 0.5685          | 0.8096 | 0.4733 | 0.7714 | 0.7549    | 286.0126 |
| 0.0558        | 6.0   | 2250 | 0.5701          | 0.5003 | 0.3431 | 0.5003 | 0.4785    | 301.6855 |
| 0.4973        | 7.0   | 2625 | 0.5521          | 1.1281 | 0.7349 | 0.9983 | 0.9983    | 295.0692 |
| 1.1935        | 8.0   | 3000 | 0.5661          | 1.3444 | 0.9964 | 1.2673 | 1.2213    | 324.3648 |
| 0.0752        | 9.0   | 3375 | 0.5531          | 1.4883 | 1.0199 | 1.4252 | 1.3979    | 301.0377 |
| 0.216         | 10.0  | 3750 | 0.5573          | 1.5516 | 1.0371 | 1.5047 | 1.4656    | 319.195  |
| 0.3619        | 11.0  | 4125 | 0.5571          | 1.2368 | 0.8055 | 1.2326 | 1.2146    | 294.4717 |
| 0.1881        | 12.0  | 4500 | 0.5293          | 1.2922 | 0.941  | 1.2149 | 1.2084    | 305.9057 |
| 0.2247        | 13.0  | 4875 | 0.5340          | 1.0581 | 0.594  | 0.9989 | 0.987     | 306.3774 |
| 0.0715        | 14.0  | 5250 | 0.5211          | 1.2905 | 0.8861 | 1.259  | 1.2143    | 321.6226 |
| 0.1851        | 15.0  | 5625 | 0.5231          | 1.4625 | 0.9737 | 1.3919 | 1.3637    | 318.4969 |
| 0.5285        | 16.0  | 6000 | 0.5154          | 1.1892 | 0.8552 | 1.1401 | 1.1061    | 313.2138 |
| 0.0482        | 17.0  | 6375 | 0.5032          | 1.1826 | 0.8687 | 1.1554 | 1.1554    | 327.1824 |
| 0.0733        | 18.0  | 6750 | 0.5193          | 1.6133 | 1.1373 | 1.5626 | 1.5085    | 317.8113 |
| 0.2814        | 19.0  | 7125 | 0.5007          | 1.5689 | 1.1133 | 1.5189 | 1.4606    | 307.7421 |
| 0.0672        | 20.0  | 7500 | 0.4959          | 1.5754 | 1.078  | 1.489  | 1.4166    | 316.6164 |
| 0.2456        | 21.0  | 7875 | 0.4966          | 1.5754 | 1.087  | 1.5005 | 1.4211    | 314.3396 |
| 0.0405        | 22.0  | 8250 | 0.4953          | 1.5754 | 1.087  | 1.5005 | 1.4211    | 310.6981 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0.dev20230811+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2