| --- |
| license: apache-2.0 |
| base_model: google/mt5-small |
| tags: |
| - summarization |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: Mymt5-small-test |
| 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. --> |
|
|
| # Mymt5-small-test |
|
|
| 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: 16.9555 |
| - Rouge1: 5.3063 |
| - Rouge2: 0.3834 |
| - Rougel: 4.7129 |
| - Rougelsum: 4.769 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 8 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | 32.0529 | 1.0 | 10 | 22.9068 | 4.148 | 0.2063 | 4.0534 | 4.0281 | |
| | 26.8483 | 2.0 | 20 | 20.5579 | 4.2091 | 0.2815 | 4.2287 | 4.2414 | |
| | 26.3936 | 3.0 | 30 | 19.4139 | 4.199 | 0.2051 | 4.1823 | 4.1637 | |
| | 24.8239 | 4.0 | 40 | 18.3165 | 4.2308 | 0.2812 | 4.2404 | 4.2749 | |
| | 24.0505 | 5.0 | 50 | 17.3909 | 4.9556 | 0.486 | 4.6229 | 4.6138 | |
| | 23.8294 | 6.0 | 60 | 17.0988 | 5.4206 | 0.5003 | 4.7981 | 4.7944 | |
| | 22.7513 | 7.0 | 70 | 16.9862 | 5.3119 | 0.3966 | 4.814 | 4.7785 | |
| | 22.836 | 8.0 | 80 | 16.9555 | 5.393 | 0.3829 | 4.7334 | 4.8031 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.40.0 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
|
|
