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---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-synthetic-data-plus-translated
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-small-synthetic-data-plus-translated
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5891
- Rouge1: 0.6390
- Rouge2: 0.5109
- Rougel: 0.6157
- Rougelsum: 0.6175
## 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: 5.6e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 14.4747 | 1.0 | 100 | 4.4435 | 0.0225 | 0.0054 | 0.0205 | 0.0215 |
| 5.9023 | 2.0 | 200 | 1.9711 | 0.1865 | 0.0791 | 0.1562 | 0.1567 |
| 3.0374 | 3.0 | 300 | 1.3288 | 0.3668 | 0.2195 | 0.3565 | 0.3567 |
| 2.1905 | 4.0 | 400 | 1.1478 | 0.4430 | 0.2741 | 0.4186 | 0.4205 |
| 1.8996 | 5.0 | 500 | 1.0408 | 0.4754 | 0.3275 | 0.4564 | 0.4574 |
| 1.6959 | 6.0 | 600 | 0.9541 | 0.5463 | 0.3972 | 0.5258 | 0.5273 |
| 1.5593 | 7.0 | 700 | 0.8942 | 0.5594 | 0.4138 | 0.5406 | 0.5426 |
| 1.4334 | 8.0 | 800 | 0.8482 | 0.6064 | 0.4683 | 0.5855 | 0.5866 |
| 1.3929 | 9.0 | 900 | 0.8106 | 0.6130 | 0.4714 | 0.5895 | 0.5911 |
| 1.2918 | 10.0 | 1000 | 0.7851 | 0.6156 | 0.4770 | 0.5929 | 0.5935 |
| 1.2362 | 11.0 | 1100 | 0.7576 | 0.6270 | 0.4894 | 0.6054 | 0.6060 |
| 1.1781 | 12.0 | 1200 | 0.7402 | 0.6257 | 0.4867 | 0.6031 | 0.6042 |
| 1.1476 | 13.0 | 1300 | 0.7212 | 0.6221 | 0.4894 | 0.6018 | 0.6029 |
| 1.1052 | 14.0 | 1400 | 0.7064 | 0.6214 | 0.4873 | 0.5983 | 0.5995 |
| 1.0667 | 15.0 | 1500 | 0.6938 | 0.6300 | 0.4972 | 0.6073 | 0.6079 |
| 1.0421 | 16.0 | 1600 | 0.6855 | 0.6265 | 0.4952 | 0.6026 | 0.6036 |
| 1.0169 | 17.0 | 1700 | 0.6748 | 0.6244 | 0.4911 | 0.6021 | 0.6029 |
| 1.0036 | 18.0 | 1800 | 0.6599 | 0.6342 | 0.5087 | 0.6130 | 0.6142 |
| 0.9828 | 19.0 | 1900 | 0.6510 | 0.6349 | 0.5090 | 0.6136 | 0.6147 |
| 0.9589 | 20.0 | 2000 | 0.6471 | 0.6370 | 0.5074 | 0.6124 | 0.6135 |
| 0.9267 | 21.0 | 2100 | 0.6400 | 0.6345 | 0.5081 | 0.6117 | 0.6127 |
| 0.9361 | 22.0 | 2200 | 0.6318 | 0.6336 | 0.5066 | 0.6126 | 0.6140 |
| 0.8992 | 23.0 | 2300 | 0.6291 | 0.6346 | 0.5066 | 0.6122 | 0.6125 |
| 0.9029 | 24.0 | 2400 | 0.6224 | 0.6367 | 0.5103 | 0.6152 | 0.6166 |
| 0.8815 | 25.0 | 2500 | 0.6159 | 0.6374 | 0.5078 | 0.6141 | 0.6157 |
| 0.8914 | 26.0 | 2600 | 0.6133 | 0.6356 | 0.5109 | 0.6120 | 0.6138 |
| 0.8548 | 27.0 | 2700 | 0.6091 | 0.6371 | 0.5089 | 0.6125 | 0.6145 |
| 0.8683 | 28.0 | 2800 | 0.6047 | 0.6387 | 0.5131 | 0.6149 | 0.6169 |
| 0.8483 | 29.0 | 2900 | 0.6020 | 0.6368 | 0.5096 | 0.6121 | 0.6133 |
| 0.8409 | 30.0 | 3000 | 0.5996 | 0.6405 | 0.5118 | 0.6139 | 0.6159 |
| 0.8407 | 31.0 | 3100 | 0.5997 | 0.6398 | 0.5123 | 0.6159 | 0.6177 |
| 0.8338 | 32.0 | 3200 | 0.5970 | 0.6385 | 0.5096 | 0.6144 | 0.6164 |
| 0.801 | 33.0 | 3300 | 0.5947 | 0.6361 | 0.5078 | 0.6122 | 0.6141 |
| 0.833 | 34.0 | 3400 | 0.5941 | 0.6386 | 0.5111 | 0.6154 | 0.6172 |
| 0.7751 | 35.0 | 3500 | 0.5921 | 0.6368 | 0.5065 | 0.6129 | 0.6148 |
| 0.8281 | 36.0 | 3600 | 0.5906 | 0.6409 | 0.5125 | 0.6183 | 0.6199 |
| 0.7803 | 37.0 | 3700 | 0.5898 | 0.6377 | 0.5097 | 0.6143 | 0.6162 |
| 0.8139 | 38.0 | 3800 | 0.5896 | 0.6398 | 0.5116 | 0.6166 | 0.6185 |
| 0.7922 | 39.0 | 3900 | 0.5894 | 0.6388 | 0.5109 | 0.6156 | 0.6174 |
| 0.8269 | 40.0 | 4000 | 0.5891 | 0.6390 | 0.5109 | 0.6157 | 0.6175 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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