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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- rouge
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model-index:
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- name: t5-base-finetune-thai-to-romanized
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# t5-base-finetune-thai-to-romanized
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 5.5823
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- Rouge1: 0.0533
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- Rouge2: 0.0
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- Rougel: 0.0543
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- Rougelsum: 0.0541
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- Gen Len: 11.3346
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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| 6.2299 | 1.0 | 1500 | 6.0909 | 0.0 | 0.0 | 0.0 | 0.0 | 12.4211 |
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| 6.0799 | 2.0 | 3000 | 5.9716 | 0.0058 | 0.0 | 0.006 | 0.0062 | 11.1185 |
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| 5.9595 | 3.0 | 4500 | 5.9016 | 0.0081 | 0.0 | 0.0082 | 0.008 | 12.1465 |
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| 5.8423 | 4.0 | 6000 | 5.7665 | 0.0364 | 0.0017 | 0.0367 | 0.0365 | 11.6982 |
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| 5.7915 | 5.0 | 7500 | 5.7470 | 0.0441 | 0.0013 | 0.0445 | 0.0442 | 10.7897 |
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| 5.7114 | 6.0 | 9000 | 5.6844 | 0.0472 | 0.0013 | 0.0476 | 0.0478 | 10.5441 |
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| 5.6555 | 7.0 | 10500 | 5.6416 | 0.0549 | 0.0013 | 0.0552 | 0.0552 | 11.1098 |
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| 5.6362 | 8.0 | 12000 | 5.6036 | 0.0493 | 0.0013 | 0.0501 | 0.0498 | 12.7922 |
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| 5.5941 | 9.0 | 13500 | 5.5895 | 0.0535 | 0.0 | 0.0544 | 0.0542 | 11.5989 |
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| 5.569 | 10.0 | 15000 | 5.5823 | 0.0533 | 0.0 | 0.0543 | 0.0541 | 11.3346 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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