Instructions to use OliverHeine/huawei-noah_TinyBERT_General_6L_768D_fold_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/huawei-noah_TinyBERT_General_6L_768D_fold_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/huawei-noah_TinyBERT_General_6L_768D_fold_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/huawei-noah_TinyBERT_General_6L_768D_fold_3") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/huawei-noah_TinyBERT_General_6L_768D_fold_3") - Notebooks
- Google Colab
- Kaggle
huawei-noah_TinyBERT_General_6L_768D_fold_3
This model is a fine-tuned version of huawei-noah/TinyBERT_General_6L_768D on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1157
- Accuracy: 0.9612
- F1: 0.9575
- Precision: 0.9632
- Recall: 0.9518
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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1269 | 1.0 | 15481 | 0.1254 | 0.9520 | 0.9467 | 0.9649 | 0.9291 |
| 0.1152 | 2.0 | 30962 | 0.1101 | 0.9592 | 0.9557 | 0.9517 | 0.9598 |
| 0.0776 | 3.0 | 46443 | 0.1157 | 0.9612 | 0.9575 | 0.9632 | 0.9518 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.6.1
- Tokenizers 0.22.2
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huawei-noah/TinyBERT_General_6L_768D