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--- |
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tags: |
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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_multilingual_XLSum-sumarizacao-PTBR |
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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_multilingual_XLSum-sumarizacao-PTBR |
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This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co/csebuetnlp/mT5_multilingual_XLSum) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3870 |
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- Rouge1: 42.0195 |
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- Rouge2: 24.9493 |
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- Rougel: 32.3653 |
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- Rougelsum: 37.9982 |
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- Gen Len: 77.0 |
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## Let's see the model in action! |
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```python |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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WHITESPACE_HANDLER = lambda k: re.sub('\s+', ' ', re.sub('\n+', ' ', k.strip())) |
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model_name = "GiordanoB/mT5_multilingual_XLSum-sumarizacao-PTBR" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForSeq2SeqLM.from_pretrained(model_name) |
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input_ids = tokenizer( |
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[WHITESPACE_HANDLER(sumariosDuplos[i])], |
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return_tensors="pt", |
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padding="max_length", |
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truncation=True, |
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max_length=512 |
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)["input_ids"] |
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output_ids = model.generate( |
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input_ids=input_ids, |
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max_length=200, |
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min_length=75, |
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no_repeat_ngram_size=2, |
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num_beams=5 |
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)[0] |
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summary = tokenizer.decode( |
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output_ids, |
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skip_special_tokens=True, |
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clean_up_tokenization_spaces=False |
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) |
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sumariosFinal.append(summary) |
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print(i,"\n",summary,"\n") |
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``` |
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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: 8 |
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- eval_batch_size: 8 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| No log | 1.0 | 15 | 1.5687 | 32.2316 | 18.9289 | 23.918 | 27.7216 | 51.5714 | |
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| No log | 2.0 | 30 | 1.4530 | 41.2297 | 26.1883 | 30.8012 | 37.1727 | 69.5714 | |
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| No log | 3.0 | 45 | 1.4043 | 40.8986 | 24.4993 | 31.349 | 36.8782 | 72.2143 | |
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| No log | 4.0 | 60 | 1.3908 | 42.1019 | 25.5555 | 32.9018 | 38.0202 | 74.5 | |
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| No log | 5.0 | 75 | 1.3870 | 42.0195 | 24.9493 | 32.3653 | 37.9982 | 77.0 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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