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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-bs32
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-bs32
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: 0.8369
- Rouge1: 0.6206
- Rouge2: 0.4859
- Rougel: 0.5972
- Rougelsum: 0.5979
## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 19.4785 | 1.0 | 38 | 11.5404 | 0.0055 | 0.0008 | 0.0051 | 0.0051 |
| 11.9977 | 2.0 | 76 | 6.4079 | 0.0101 | 0.0015 | 0.0089 | 0.0094 |
| 7.5027 | 3.0 | 114 | 3.0626 | 0.0542 | 0.0093 | 0.0482 | 0.0487 |
| 4.8939 | 4.0 | 152 | 2.2496 | 0.0492 | 0.0182 | 0.0429 | 0.0437 |
| 3.64 | 5.0 | 190 | 1.7984 | 0.1870 | 0.0826 | 0.1598 | 0.1601 |
| 2.8662 | 6.0 | 228 | 1.4518 | 0.1852 | 0.0916 | 0.1653 | 0.1659 |
| 2.4493 | 7.0 | 266 | 1.3124 | 0.4183 | 0.2586 | 0.4014 | 0.4026 |
| 2.1362 | 8.0 | 304 | 1.2444 | 0.4386 | 0.2716 | 0.4176 | 0.4196 |
| 1.9923 | 9.0 | 342 | 1.1876 | 0.4587 | 0.3034 | 0.4387 | 0.4404 |
| 1.8438 | 10.0 | 380 | 1.1486 | 0.5198 | 0.3637 | 0.4979 | 0.4988 |
| 1.7212 | 11.0 | 418 | 1.1031 | 0.5402 | 0.3848 | 0.5160 | 0.5169 |
| 1.6315 | 12.0 | 456 | 1.0707 | 0.5556 | 0.3999 | 0.5325 | 0.5341 |
| 1.5623 | 13.0 | 494 | 1.0437 | 0.5808 | 0.4309 | 0.5583 | 0.5593 |
| 1.5269 | 14.0 | 532 | 1.0188 | 0.5986 | 0.4540 | 0.5773 | 0.5772 |
| 1.4668 | 15.0 | 570 | 0.9982 | 0.5922 | 0.4511 | 0.5731 | 0.5737 |
| 1.4357 | 16.0 | 608 | 0.9777 | 0.5965 | 0.4549 | 0.5768 | 0.5773 |
| 1.3684 | 17.0 | 646 | 0.9623 | 0.6123 | 0.4722 | 0.5901 | 0.5907 |
| 1.3675 | 18.0 | 684 | 0.9461 | 0.6135 | 0.4771 | 0.5915 | 0.5919 |
| 1.3285 | 19.0 | 722 | 0.9324 | 0.6150 | 0.4754 | 0.5916 | 0.5918 |
| 1.288 | 20.0 | 760 | 0.9271 | 0.6179 | 0.4803 | 0.5964 | 0.5968 |
| 1.2529 | 21.0 | 798 | 0.9129 | 0.6156 | 0.4789 | 0.5939 | 0.5940 |
| 1.2216 | 22.0 | 836 | 0.9017 | 0.6163 | 0.4817 | 0.5941 | 0.5941 |
| 1.2322 | 23.0 | 874 | 0.8948 | 0.6208 | 0.4839 | 0.5985 | 0.5986 |
| 1.2062 | 24.0 | 912 | 0.8838 | 0.6139 | 0.4778 | 0.5904 | 0.5912 |
| 1.1642 | 25.0 | 950 | 0.8761 | 0.6150 | 0.4818 | 0.5939 | 0.5951 |
| 1.1699 | 26.0 | 988 | 0.8759 | 0.6152 | 0.4794 | 0.5929 | 0.5932 |
| 1.1428 | 27.0 | 1026 | 0.8662 | 0.6158 | 0.4806 | 0.5935 | 0.5946 |
| 1.195 | 28.0 | 1064 | 0.8609 | 0.6126 | 0.4758 | 0.5898 | 0.5908 |
| 1.1619 | 29.0 | 1102 | 0.8568 | 0.6152 | 0.4776 | 0.5924 | 0.5936 |
| 1.1172 | 30.0 | 1140 | 0.8548 | 0.6181 | 0.4788 | 0.5951 | 0.5964 |
| 1.1141 | 31.0 | 1178 | 0.8526 | 0.6148 | 0.4766 | 0.5904 | 0.5914 |
| 1.1176 | 32.0 | 1216 | 0.8488 | 0.6201 | 0.4834 | 0.5963 | 0.5972 |
| 1.0959 | 33.0 | 1254 | 0.8475 | 0.6225 | 0.4847 | 0.5983 | 0.5993 |
| 1.0954 | 34.0 | 1292 | 0.8437 | 0.6220 | 0.4859 | 0.5987 | 0.5986 |
| 1.0844 | 35.0 | 1330 | 0.8420 | 0.6206 | 0.4851 | 0.5969 | 0.5974 |
| 1.1041 | 36.0 | 1368 | 0.8398 | 0.6222 | 0.4865 | 0.5991 | 0.5992 |
| 1.0736 | 37.0 | 1406 | 0.8386 | 0.6225 | 0.4867 | 0.5991 | 0.6001 |
| 1.0816 | 38.0 | 1444 | 0.8376 | 0.6229 | 0.4871 | 0.5994 | 0.6001 |
| 1.0537 | 39.0 | 1482 | 0.8372 | 0.6242 | 0.4876 | 0.6004 | 0.6013 |
| 1.092 | 40.0 | 1520 | 0.8369 | 0.6206 | 0.4859 | 0.5972 | 0.5979 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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