gui8600k's picture
gpt4_fine_tuned_bert_multilingual_params_careful
55f43df verified
metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: results_fine_tune_gpt40_original_careful
    results: []

results_fine_tune_gpt40_original_careful

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

  • Loss: 0.0019
  • Accuracy: 0.9993

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 32
  • seed: 42
  • 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
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0049 0.8881 500 0.0082 0.9987
0.0056 1.7762 1000 0.0226 0.9973
0.0062 2.6643 1500 0.0003 1.0
0.0031 3.5524 2000 0.0009 0.9993
0.0006 4.4405 2500 0.0019 0.9993

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu124
  • Datasets 2.17.0
  • Tokenizers 0.21.0