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---
license: apache-2.0
base_model: google/mt5-base
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 [google/mt5-base](https://huggingface.co./google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5590
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- 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: 5e-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
- lr_scheduler_warmup_steps: 5000
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 19.6644 | 1.0 | 188 | 13.7553 | 0.7175 | 0.0 | 0.7387 | 0.7032 | 12.283 |
| 10.6133 | 2.0 | 376 | 11.3168 | 0.7175 | 0.0 | 0.7387 | 0.7032 | 13.4654 |
| 10.1742 | 3.0 | 564 | 7.7772 | 0.7175 | 0.0 | 0.7387 | 0.7032 | 15.9874 |
| 2.8326 | 4.0 | 752 | 4.6011 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 19.0 |
| 4.2099 | 5.0 | 940 | 5.8284 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 15.8805 |
| 1.7867 | 6.0 | 1128 | 2.0588 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 15.761 |
| 3.6568 | 7.0 | 1316 | 1.7242 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 12.9371 |
| 4.1534 | 8.0 | 1504 | 1.4302 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 15.1761 |
| 0.9298 | 9.0 | 1692 | 1.3871 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 14.3711 |
| 1.5429 | 10.0 | 1880 | 1.1574 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 18.4969 |
| 1.1307 | 11.0 | 2068 | 1.0076 | 0.8804 | 0.1144 | 0.8573 | 0.8336 | 19.0 |
| 0.9566 | 12.0 | 2256 | 0.9130 | 0.7498 | 0.0 | 0.7731 | 0.7387 | 19.0 |
| 0.6761 | 13.0 | 2444 | 0.8454 | 0.8804 | 0.1144 | 0.8573 | 0.8336 | 19.0 |
| 0.1983 | 14.0 | 2632 | 0.7835 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 |
| 0.5771 | 15.0 | 2820 | 0.7411 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 |
| 1.1574 | 16.0 | 3008 | 0.7099 | 0.3594 | 0.2648 | 0.3594 | 0.3594 | 19.0 |
| 0.1504 | 17.0 | 3196 | 0.6689 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 |
| 0.1265 | 18.0 | 3384 | 0.6576 | 0.3594 | 0.2648 | 0.3594 | 0.3594 | 19.0 |
| 0.6688 | 19.0 | 3572 | 0.6355 | 0.3594 | 0.2648 | 0.3594 | 0.3594 | 19.0 |
| 0.1103 | 20.0 | 3760 | 0.6101 | 0.5391 | 0.3972 | 0.5391 | 0.5391 | 19.0 |
| 0.4472 | 21.0 | 3948 | 0.6018 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 |
| 0.0696 | 22.0 | 4136 | 0.5804 | 0.2459 | 0.1324 | 0.2459 | 0.2223 | 19.0 |
| 0.2857 | 23.0 | 4324 | 0.5685 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 |
| 0.4744 | 24.0 | 4512 | 0.5475 | 0.2459 | 0.1324 | 0.2459 | 0.2223 | 19.0 |
| 0.2841 | 25.0 | 4700 | 0.5590 | 0.0 | 0.0 | 0.0 | 0.0 | 19.0 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0.dev20230811+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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