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--- |
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license: apache-2.0 |
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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-text-sum-3 |
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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-text-sum-3 |
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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: 2.3392 |
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- Rouge1: 21.71 |
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- Rouge2: 6.65 |
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- Rougel: 21.31 |
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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: 0.0001 |
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- train_batch_size: 10 |
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- eval_batch_size: 10 |
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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: 40 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:| |
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| 4.6563 | 1.61 | 500 | 2.5975 | 16.78 | 5.15 | 16.64 | |
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| 3.1112 | 3.22 | 1000 | 2.4856 | 17.05 | 5.31 | 16.8 | |
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| 2.876 | 4.82 | 1500 | 2.4217 | 18.1 | 5.36 | 17.85 | |
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| 2.7557 | 6.43 | 2000 | 2.4423 | 18.65 | 5.76 | 18.27 | |
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| 2.6327 | 8.04 | 2500 | 2.4024 | 19.44 | 6.02 | 19.16 | |
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| 2.5444 | 9.65 | 3000 | 2.3581 | 18.76 | 5.58 | 18.4 | |
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| 2.4373 | 11.25 | 3500 | 2.3654 | 19.87 | 6.48 | 19.43 | |
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| 2.4058 | 12.86 | 4000 | 2.3767 | 19.87 | 5.96 | 19.43 | |
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| 2.3404 | 14.47 | 4500 | 2.3602 | 20.01 | 5.94 | 19.64 | |
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| 2.2882 | 16.08 | 5000 | 2.3392 | 21.71 | 6.65 | 21.31 | |
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| 2.2263 | 17.68 | 5500 | 2.3520 | 20.31 | 6.3 | 20.04 | |
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| 2.1948 | 19.29 | 6000 | 2.3699 | 21.2 | 6.84 | 20.81 | |
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| 2.154 | 20.9 | 6500 | 2.3472 | 20.39 | 5.82 | 19.94 | |
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| 2.1218 | 22.51 | 7000 | 2.3679 | 20.07 | 6.38 | 19.69 | |
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| 2.073 | 24.12 | 7500 | 2.3457 | 19.7 | 5.8 | 19.2 | |
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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 2.10.1 |
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- Tokenizers 0.13.2 |
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