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---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mT5_multilingual_XLSum-sumarizacao-PTBR
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mT5_multilingual_XLSum-sumarizacao-PTBR
This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co/csebuetnlp/mT5_multilingual_XLSum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3870
- Rouge1: 42.0195
- Rouge2: 24.9493
- Rougel: 32.3653
- Rougelsum: 37.9982
- Gen Len: 77.0
## Model description
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
WHITESPACE_HANDLER = lambda k: re.sub('\s+', ' ', re.sub('\n+', ' ', k.strip()))
model_name = "GiordanoB/mT5_multilingual_XLSum-sumarizacao-PTBR"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
input_ids = tokenizer(
[WHITESPACE_HANDLER(sumariosDuplos[i])],
return_tensors="pt",
padding="max_length",
truncation=True,
max_length=512
)["input_ids"]
output_ids = model.generate(
input_ids=input_ids,
max_length=200,
min_length=75,
no_repeat_ngram_size=2,
num_beams=5
)[0]
summary = tokenizer.decode(
output_ids,
skip_special_tokens=True,
clean_up_tokenization_spaces=False
)
sumariosFinal.append(summary)
print(i,"\n",summary,"\n")
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log | 1.0 | 15 | 1.5687 | 32.2316 | 18.9289 | 23.918 | 27.7216 | 51.5714 |
| No log | 2.0 | 30 | 1.4530 | 41.2297 | 26.1883 | 30.8012 | 37.1727 | 69.5714 |
| No log | 3.0 | 45 | 1.4043 | 40.8986 | 24.4993 | 31.349 | 36.8782 | 72.2143 |
| No log | 4.0 | 60 | 1.3908 | 42.1019 | 25.5555 | 32.9018 | 38.0202 | 74.5 |
| No log | 5.0 | 75 | 1.3870 | 42.0195 | 24.9493 | 32.3653 | 37.9982 | 77.0 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
|