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--- |
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license: apache-2.0 |
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base_model: google/mt5-small |
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tags: |
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- summarization |
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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: mt5-small-finetuned-amazon-en-zh |
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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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# mt5-small-finetuned-amazon-en-zh |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.1950 |
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- Rouge1: 15.5597 |
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- Rouge2: 6.7429 |
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- Rougel: 15.1794 |
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- Rougelsum: 15.063 |
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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: 5.6e-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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
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| 8.0083 | 1.0 | 838 | 3.5147 | 13.2577 | 6.0411 | 12.9176 | 12.8293 | |
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| 4.0156 | 2.0 | 1676 | 3.3382 | 14.2493 | 6.3606 | 13.9407 | 13.7391 | |
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| 3.6492 | 3.0 | 2514 | 3.2576 | 15.915 | 7.4853 | 15.8512 | 15.72 | |
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| 3.473 | 4.0 | 3352 | 3.2266 | 16.3162 | 6.6844 | 15.9962 | 15.8693 | |
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| 3.3509 | 5.0 | 4190 | 3.2010 | 15.2992 | 6.2211 | 14.9191 | 14.8807 | |
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| 3.2828 | 6.0 | 5028 | 3.2008 | 15.379 | 6.38 | 15.1408 | 15.0073 | |
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| 3.2304 | 7.0 | 5866 | 3.2003 | 15.8089 | 6.7429 | 15.4859 | 15.3334 | |
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| 3.191 | 8.0 | 6704 | 3.1950 | 15.5597 | 6.7429 | 15.1794 | 15.063 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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