Instructions to use OliverHeine/google_mobilebert-uncased_fold_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/google_mobilebert-uncased_fold_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/google_mobilebert-uncased_fold_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/google_mobilebert-uncased_fold_1") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/google_mobilebert-uncased_fold_1") - Notebooks
- Google Colab
- Kaggle
google_mobilebert-uncased_fold_1
This model is a fine-tuned version of google/mobilebert-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1152
- Accuracy: 0.9599
- F1: 0.9558
- Precision: 0.9651
- Recall: 0.9468
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 |
|---|---|---|---|---|---|---|---|
| 1.3193 | 1.0 | 15481 | 0.1280 | 0.9516 | 0.9469 | 0.9543 | 0.9395 |
| 0.0943 | 2.0 | 30962 | 0.1130 | 0.9580 | 0.9537 | 0.9634 | 0.9443 |
| 0.0854 | 3.0 | 46443 | 0.1152 | 0.9599 | 0.9558 | 0.9651 | 0.9468 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.6.1
- Tokenizers 0.22.2
- Downloads last month
- -
Model tree for OliverHeine/google_mobilebert-uncased_fold_1
Base model
google/mobilebert-uncased