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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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datasets: |
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- thaisum |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5_thaisum_model |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: thaisum |
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type: thaisum |
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config: thaisum |
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split: validation |
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args: thaisum |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.1432 |
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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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# mt5_thaisum_model |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the thaisum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3540 |
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- Rouge1: 0.1432 |
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- Rouge2: 0.041 |
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- Rougel: 0.1423 |
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- Rougelsum: 0.142 |
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- Gen Len: 18.933 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 4 |
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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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| 2.4271 | 1.0 | 2500 | 0.3976 | 0.1306 | 0.0372 | 0.1302 | 0.1299 | 18.9665 | |
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| 2.1992 | 2.0 | 5000 | 0.3720 | 0.1392 | 0.0376 | 0.1382 | 0.1384 | 18.922 | |
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| 2.1687 | 3.0 | 7500 | 0.3599 | 0.1401 | 0.0391 | 0.1394 | 0.1389 | 18.9215 | |
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| 2.1096 | 4.0 | 10000 | 0.3540 | 0.1432 | 0.041 | 0.1423 | 0.142 | 18.933 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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