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---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mT5-fine-tune
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-fine-tune
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: 2.5256
- Rouge1: 0.0822
- Rouge2: 0.0244
- Rougel: 0.0813
- Rougelsum: 0.0814
- Gen Len: 18.9803
- Chrf Score: 20.301
- Chrf Char Order: 6
- Chrf Word Order: 0
- Chrf Beta: 2
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Chrf Score | Chrf Char Order | Chrf Word Order | Chrf Beta |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:----------:|:---------------:|:---------------:|:---------:|
| 3.5479 | 1.0 | 1951 | 2.7435 | 0.0672 | 0.021 | 0.0666 | 0.0667 | 18.9323 | 19.2495 | 6 | 0 | 2 |
| 3.1717 | 2.0 | 3902 | 2.6452 | 0.0746 | 0.0207 | 0.0738 | 0.0737 | 18.9814 | 20.1079 | 6 | 0 | 2 |
| 3.0151 | 3.0 | 5853 | 2.6014 | 0.0834 | 0.0243 | 0.0826 | 0.0823 | 18.9891 | 20.2875 | 6 | 0 | 2 |
| 2.95 | 4.0 | 7804 | 2.5647 | 0.0765 | 0.0218 | 0.0757 | 0.0757 | 18.981 | 20.2327 | 6 | 0 | 2 |
| 2.8592 | 5.0 | 9755 | 2.5480 | 0.0822 | 0.0242 | 0.0814 | 0.0813 | 18.9819 | 20.3982 | 6 | 0 | 2 |
| 2.8214 | 6.0 | 11706 | 2.5317 | 0.0841 | 0.0255 | 0.0831 | 0.083 | 18.9764 | 20.3935 | 6 | 0 | 2 |
| 2.789 | 7.0 | 13657 | 2.5256 | 0.0822 | 0.0244 | 0.0813 | 0.0814 | 18.9803 | 20.301 | 6 | 0 | 2 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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