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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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