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clasificador-ser-estar-window-3-bert-base

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bert
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metadata
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
  - generated_from_trainer
metrics:
  - recall
  - precision
model-index:
  - name: clasificador-ser-estar-window-3-bert-base
    results: []

clasificador-ser-estar-window-3-bert-base

This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4416
  • F1 Score: 0.8648
  • Recall: 0.9578
  • Precision: 0.7882
  • Roc Auc: 0.8802

Model description

More information needed

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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss F1 Score Recall Precision Roc Auc
No log 1.0 25 0.6602 0.7465 1.0 0.5955 0.6476
No log 2.0 50 0.5149 0.8342 0.9873 0.7222 0.8281
No log 3.0 75 0.4397 0.8561 0.9916 0.7532 0.8710
No log 4.0 100 0.4293 0.8566 0.9325 0.7921 0.8897
No log 5.0 125 0.4076 0.8566 0.9325 0.7921 0.8882
No log 6.0 150 0.4416 0.8648 0.9578 0.7882 0.8802
No log 7.0 175 0.4894 0.8499 0.9198 0.7899 0.8800
No log 8.0 200 0.5129 0.8577 0.9283 0.7971 0.8907
No log 9.0 225 0.5474 0.8532 0.9198 0.7956 0.8817
No log 10.0 250 0.6858 0.8377 0.8819 0.7977 0.8750
No log 11.0 275 0.6811 0.8465 0.9072 0.7934 0.8740
No log 12.0 300 0.7265 0.8538 0.9367 0.7845 0.8761
No log 13.0 325 0.7422 0.8532 0.9198 0.7956 0.8825
No log 14.0 350 0.8648 0.8409 0.9030 0.7868 0.8743
No log 15.0 375 0.8326 0.8498 0.9072 0.7993 0.8816
No log 16.0 400 0.8516 0.8504 0.9114 0.7970 0.8776
No log 17.0 425 0.8633 0.8487 0.9114 0.7941 0.8862
No log 18.0 450 0.9064 0.8475 0.9030 0.7985 0.8856
No log 19.0 475 0.9145 0.8475 0.9030 0.7985 0.8856
0.2549 20.0 500 0.9146 0.8475 0.9030 0.7985 0.8860

Framework versions

  • Transformers 4.48.3
  • Pytorch 2.5.1+cu124
  • Datasets 3.3.2
  • Tokenizers 0.21.0