--- library_name: transformers language: - en base_model: Hartunka/tiny_bert_rand_10_v2 tags: - generated_from_trainer datasets: - glue metrics: - spearmanr model-index: - name: tiny_bert_rand_10_v2_stsb results: - task: name: Text Classification type: text-classification dataset: name: GLUE STSB type: glue args: stsb metrics: - name: Spearmanr type: spearmanr value: 0.11027095360407262 --- # tiny_bert_rand_10_v2_stsb This model is a fine-tuned version of [Hartunka/tiny_bert_rand_10_v2](https://huggingface.co/Hartunka/tiny_bert_rand_10_v2) on the GLUE STSB dataset. It achieves the following results on the evaluation set: - Loss: 2.2278 - Pearson: 0.1029 - Spearmanr: 0.1103 - Combined Score: 0.1066 ## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| | 3.1623 | 1.0 | 23 | 2.2278 | 0.1029 | 0.1103 | 0.1066 | | 2.0283 | 2.0 | 46 | 2.6435 | 0.0808 | 0.0590 | 0.0699 | | 1.8414 | 3.0 | 69 | 2.4582 | 0.1896 | 0.1824 | 0.1860 | | 1.6228 | 4.0 | 92 | 2.4701 | 0.2441 | 0.2441 | 0.2441 | | 1.3269 | 5.0 | 115 | 2.4297 | 0.2678 | 0.2654 | 0.2666 | | 1.0809 | 6.0 | 138 | 2.4510 | 0.2983 | 0.3000 | 0.2992 | ### Framework versions - Transformers 4.50.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.21.1