---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: deed_summarization_mt5_version_1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# deed_summarization_mt5_version_1

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5863
- Rouge1: 1.0138
- Rouge2: 0.6875
- Rougel: 1.0233
- Rougelsum: 1.0941
- Gen Len: 288.1509

## 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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 25.5422       | 1.0   | 375  | 16.6467         | 0.6477 | 0.0    | 0.6383 | 0.6639    | 25.0     |
| 11.9626       | 2.0   | 750  | 13.5214         | 0.6633 | 0.0    | 0.6553 | 0.6745    | 38.5912  |
| 10.1002       | 3.0   | 1125 | 7.4294          | 0.7257 | 0.0    | 0.7163 | 0.7264    | 386.6164 |
| 2.8844        | 4.0   | 1500 | 2.8574          | 0.7257 | 0.0    | 0.7163 | 0.7264    | 499.0    |
| 4.1183        | 5.0   | 1875 | 9.6893          | 0.7257 | 0.0    | 0.7163 | 0.7264    | 499.0    |
| 1.4443        | 6.0   | 2250 | 2.4224          | 0.7257 | 0.0    | 0.7163 | 0.7264    | 466.7673 |
| 3.8512        | 7.0   | 2625 | 1.5813          | 0.7257 | 0.0    | 0.7163 | 0.7264    | 432.4717 |
| 8.6527        | 8.0   | 3000 | 1.4532          | 0.7257 | 0.0    | 0.7163 | 0.7264    | 480.6164 |
| 0.5302        | 9.0   | 3375 | 1.1597          | 0.7257 | 0.0    | 0.7163 | 0.7264    | 419.239  |
| 1.2311        | 10.0  | 3750 | 0.9806          | 0.9895 | 0.1006 | 0.9135 | 0.9189    | 383.6855 |
| 0.8903        | 11.0  | 4125 | 0.8961          | 0.9609 | 0.1578 | 0.8871 | 0.8934    | 376.6038 |
| 0.8742        | 12.0  | 4500 | 0.8109          | 1.1104 | 0.2243 | 1.0038 | 1.007     | 388.3648 |
| 0.5934        | 13.0  | 4875 | 0.7588          | 0.3145 | 0.2287 | 0.3145 | 0.3145    | 341.717  |
| 0.1715        | 14.0  | 5250 | 0.7073          | 0.2795 | 0.2013 | 0.2795 | 0.2795    | 333.434  |
| 0.4363        | 15.0  | 5625 | 0.6780          | 0.4368 | 0.2287 | 0.4368 | 0.4368    | 326.7044 |
| 1.0736        | 16.0  | 6000 | 0.6647          | 0.7163 | 0.5169 | 0.7512 | 0.7512    | 299.4151 |
| 0.1069        | 17.0  | 6375 | 0.6294          | 0.856  | 0.6038 | 0.863  | 0.8595    | 312.434  |
| 0.1434        | 18.0  | 6750 | 0.6358          | 0.7512 | 0.5222 | 0.7862 | 0.808     | 291.4403 |
| 0.4344        | 19.0  | 7125 | 0.6164          | 1.1082 | 0.7576 | 1.1305 | 1.1574    | 304.7484 |
| 0.1038        | 20.0  | 7500 | 0.6066          | 0.8572 | 0.6108 | 0.8758 | 0.9085    | 297.3145 |
| 0.5519        | 21.0  | 7875 | 0.5972          | 0.4354 | 0.2935 | 0.5382 | 0.5382    | 281.5786 |
| 0.0804        | 22.0  | 8250 | 0.5994          | 0.6464 | 0.5583 | 0.7741 | 0.7794    | 305.805  |
| 0.3696        | 23.0  | 8625 | 0.5884          | 0.6362 | 0.3246 | 0.6362 | 0.6362    | 291.434  |
| 0.3966        | 24.0  | 9000 | 0.5852          | 0.7133 | 0.408  | 0.7311 | 0.8082    | 281.9119 |
| 0.3484        | 25.0  | 9375 | 0.5863          | 1.0138 | 0.6875 | 1.0233 | 1.0941    | 288.1509 |


### Framework versions

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