| ---
|
| library_name: transformers
|
| license: apache-2.0
|
| base_model: google/mobilebert-uncased
|
| tags:
|
| - generated_from_trainer
|
| metrics:
|
| - accuracy
|
| - f1
|
| - precision
|
| - recall
|
| model-index:
|
| - name: google_mobilebert-uncased_fold_6
|
| 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. -->
|
|
|
| # google_mobilebert-uncased_fold_6
|
|
|
| This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the None dataset.
|
| It achieves the following results on the evaluation set:
|
| - Loss: 0.1170
|
| - Accuracy: 0.9588
|
| - F1: 0.9548
|
| - Precision: 0.9603
|
| - Recall: 0.9493
|
|
|
| ## 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: 2e-05
|
| - train_batch_size: 40
|
| - eval_batch_size: 40
|
| - seed: 42
|
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
| - lr_scheduler_type: linear
|
| - num_epochs: 3
|
|
|
| ### Training results
|
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
|
| | 0.1319 | 1.0 | 15481 | 0.1306 | 0.9502 | 0.9452 | 0.9520 | 0.9386 |
|
| | 0.0944 | 2.0 | 30962 | 0.1145 | 0.9567 | 0.9525 | 0.9573 | 0.9477 |
|
| | 0.0772 | 3.0 | 46443 | 0.1170 | 0.9588 | 0.9548 | 0.9603 | 0.9493 |
|
|
|
|
|
| ### Framework versions
|
|
|
| - Transformers 5.3.0
|
| - Pytorch 2.10.0+cu128
|
| - Datasets 4.6.1
|
| - Tokenizers 0.22.2
|
|
|
