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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-base-wikinewssum-polish |
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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-wikinewssum-polish |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3179 |
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- Rouge1: 7.911 |
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- Rouge2: 3.2189 |
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- Rougel: 6.7856 |
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- Rougelsum: 7.4485 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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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| No log | 1.0 | 315 | 2.5391 | 5.9874 | 2.3594 | 5.1303 | 5.6116 | |
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| No log | 2.0 | 630 | 2.4446 | 7.7294 | 3.0152 | 6.6024 | 7.2757 | |
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| No log | 3.0 | 945 | 2.3912 | 7.6451 | 2.9785 | 6.5714 | 7.2011 | |
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| 3.5311 | 4.0 | 1260 | 2.3720 | 7.8007 | 3.0913 | 6.7067 | 7.3451 | |
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| 3.5311 | 5.0 | 1575 | 2.3411 | 7.8374 | 3.1208 | 6.7288 | 7.3459 | |
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| 3.5311 | 6.0 | 1890 | 2.3354 | 7.8664 | 3.1655 | 6.762 | 7.4364 | |
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| 3.5311 | 7.0 | 2205 | 2.3175 | 7.9529 | 3.2225 | 6.8438 | 7.4904 | |
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| 2.692 | 8.0 | 2520 | 2.3179 | 7.911 | 3.2189 | 6.7856 | 7.4485 | |
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### Framework versions |
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- Transformers 4.13.0 |
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- Pytorch 1.10.1 |
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- Datasets 1.16.1 |
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- Tokenizers 0.10.3 |
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