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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-spanish |
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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-spanish |
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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: 2.2394 |
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- Rouge1: 7.9732 |
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- Rouge2: 3.5041 |
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- Rougel: 6.6713 |
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- Rougelsum: 7.5229 |
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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 | 528 | 2.3707 | 6.687 | 2.9169 | 5.6793 | 6.2978 | |
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| No log | 2.0 | 1056 | 2.3140 | 7.9518 | 3.4529 | 6.7265 | 7.4984 | |
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| No log | 3.0 | 1584 | 2.2848 | 7.9708 | 3.5344 | 6.7272 | 7.534 | |
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| No log | 4.0 | 2112 | 2.2668 | 8.0252 | 3.5323 | 6.7319 | 7.5819 | |
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| 3.2944 | 5.0 | 2640 | 2.2532 | 8.0143 | 3.534 | 6.7155 | 7.582 | |
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| 3.2944 | 6.0 | 3168 | 2.2399 | 7.9525 | 3.4849 | 6.6716 | 7.5155 | |
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| 3.2944 | 7.0 | 3696 | 2.2376 | 7.9405 | 3.4661 | 6.6559 | 7.5043 | |
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| 3.2944 | 8.0 | 4224 | 2.2394 | 7.9732 | 3.5041 | 6.6713 | 7.5229 | |
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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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