--- language: - en base_model: Hartunka/tiny_bert_km_100_v1 tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: tiny_bert_km_100_v1_qnli results: - task: name: Text Classification type: text-classification dataset: name: GLUE QNLI type: glue args: qnli metrics: - name: Accuracy type: accuracy value: 0.632985539081091 --- # tiny_bert_km_100_v1_qnli This model is a fine-tuned version of [Hartunka/tiny_bert_km_100_v1](https://huggingface.co/Hartunka/tiny_bert_km_100_v1) on the GLUE QNLI dataset. It achieves the following results on the evaluation set: - Loss: 0.6400 - Accuracy: 0.6330 ## 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: 256 - eval_batch_size: 256 - seed: 10 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.6679 | 1.0 | 410 | 0.6485 | 0.6136 | | 0.6394 | 2.0 | 820 | 0.6451 | 0.6251 | | 0.5956 | 3.0 | 1230 | 0.6400 | 0.6330 | | 0.5331 | 4.0 | 1640 | 0.7006 | 0.6244 | | 0.4637 | 5.0 | 2050 | 0.7612 | 0.6196 | | 0.3991 | 6.0 | 2460 | 0.8429 | 0.6224 | | 0.3391 | 7.0 | 2870 | 0.9845 | 0.6163 | | 0.2843 | 8.0 | 3280 | 1.0887 | 0.6176 | ### Framework versions - Transformers 4.40.0 - Pytorch 2.6.0+cu124 - Datasets 3.5.0 - Tokenizers 0.19.1