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license: apache-2.0 |
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tags: |
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- summarization |
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- english |
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- en |
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- mt5 |
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- Abstractive Summarization |
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- generated_from_trainer |
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datasets: |
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- xlsum |
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model-index: |
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- name: mt5-base-finetuned-english |
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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-base-finetuned-english |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the xlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.3271 |
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- Rouge-1: 31.7 |
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- Rouge-2: 11.83 |
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- Rouge-l: 26.43 |
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- Gen Len: 18.88 |
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- Bertscore: 74.3 |
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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: 0.0005 |
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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: 8 |
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- total_train_batch_size: 32 |
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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: 5 |
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- label_smoothing_factor: 0.1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:| |
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| 4.174 | 1.0 | 3125 | 3.5662 | 27.01 | 7.95 | 22.16 | 18.91 | 72.62 | |
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| 3.6577 | 2.0 | 6250 | 3.4304 | 28.84 | 9.09 | 23.64 | 18.87 | 73.32 | |
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| 3.4526 | 3.0 | 9375 | 3.3691 | 29.69 | 9.96 | 24.58 | 18.84 | 73.69 | |
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| 3.3091 | 4.0 | 12500 | 3.3368 | 30.38 | 10.32 | 25.1 | 18.9 | 73.9 | |
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| 3.2056 | 5.0 | 15625 | 3.3271 | 30.7 | 10.65 | 25.45 | 18.89 | 73.99 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.2.0 |
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- Tokenizers 0.12.1 |
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