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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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- generated_from_trainer |
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model-index: |
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- name: ntu_adl_summarization_mt5_s |
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results: [] |
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datasets: |
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- xjlulu/ntu_adl_summarization |
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language: |
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- zh |
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metrics: |
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- rouge |
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pipeline_tag: summarization |
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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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# ntu_adl_summarization_mt5_s |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6583 |
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- Rouge-1: 21.9729 |
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- Rouge-2: 7.6735 |
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- Rouge-l: 19.7497 |
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- Ave Gen Len: 17.3098 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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 | Rouge-1 | Rouge-2 | Rouge-l | Ave Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-----------:| |
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| 5.4447 | 1.0 | 1357 | 4.1235 | 17.7916 | 5.9785 | 16.5599 | 12.7161 | |
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| 4.7463 | 2.0 | 2714 | 3.9569 | 19.6608 | 6.7631 | 18.0768 | 14.8245 | |
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| 4.5203 | 3.0 | 4071 | 3.8545 | 20.5626 | 7.0737 | 18.7628 | 16.3307 | |
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| 4.4285 | 4.0 | 5428 | 3.7825 | 21.0690 | 7.2030 | 19.0863 | 16.7841 | |
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| 4.3196 | 5.0 | 6785 | 3.7269 | 21.2881 | 7.3307 | 19.2588 | 16.9276 | |
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| 4.2662 | 6.0 | 8142 | 3.7027 | 21.5793 | 7.5122 | 19.4806 | 17.0333 | |
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| 4.2057 | 7.0 | 9499 | 3.6764 | 21.7949 | 7.5987 | 19.6082 | 17.1811 | |
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| 4.1646 | 8.0 | 10856 | 3.6671 | 21.8164 | 7.5705 | 19.6207 | 17.2550 | |
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| 4.1399 | 9.0 | 12213 | 3.6602 | 21.9381 | 7.6577 | 19.7089 | 17.3014 | |
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| 4.1479 | 10.0 | 13570 | 3.6583 | 21.9729 | 7.6735 | 19.7497 | 17.3098 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
