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End of training
Browse files- README.md +70 -0
- model.safetensors +1 -1
README.md
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---
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license: mit
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base_model: neuralmind/bert-base-portuguese-cased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: newsdata-bertimbal
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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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# newsdata-bertimbal
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This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7455
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- Accuracy: 0.8743
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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: 2e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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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: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:------:|:-----:|:---------------:|:--------:|
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| 0.8448 | 0.0859 | 5000 | 1.1296 | 0.8044 |
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| 0.7301 | 0.1718 | 10000 | 1.0056 | 0.8258 |
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| 0.6827 | 0.2577 | 15000 | 0.9388 | 0.8464 |
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| 0.6221 | 0.3436 | 20000 | 0.9358 | 0.8502 |
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| 0.5611 | 0.4295 | 25000 | 0.8983 | 0.8567 |
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| 0.5291 | 0.5155 | 30000 | 0.8503 | 0.8575 |
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| 0.4202 | 0.6014 | 35000 | 0.8353 | 0.8656 |
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| 0.5436 | 0.6873 | 40000 | 0.7476 | 0.8706 |
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| 0.4814 | 0.7732 | 45000 | 0.7863 | 0.8669 |
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| 0.4853 | 0.8591 | 50000 | 0.7284 | 0.8720 |
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| 0.39 | 0.9450 | 55000 | 0.7455 | 0.8743 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
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size 435851416
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version https://git-lfs.github.com/spec/v1
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size 435851416
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