--- library_name: transformers language: - en base_model: Hartunka/tiny_bert_rand_5_v2 tags: - generated_from_trainer datasets: - glue metrics: - spearmanr model-index: - name: tiny_bert_rand_5_v2_stsb results: - task: name: Text Classification type: text-classification dataset: name: GLUE STSB type: glue args: stsb metrics: - name: Spearmanr type: spearmanr value: 0.2033573197630174 --- # tiny_bert_rand_5_v2_stsb This model is a fine-tuned version of [Hartunka/tiny_bert_rand_5_v2](https://huggingface.co/Hartunka/tiny_bert_rand_5_v2) on the GLUE STSB dataset. It achieves the following results on the evaluation set: - Loss: 2.2907 - Pearson: 0.2162 - Spearmanr: 0.2034 - Combined Score: 0.2098 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| | 3.1743 | 1.0 | 23 | 2.2973 | 0.1229 | 0.1070 | 0.1149 | | 2.0355 | 2.0 | 46 | 2.5679 | 0.1150 | 0.1022 | 0.1086 | | 1.8438 | 3.0 | 69 | 2.2907 | 0.2162 | 0.2034 | 0.2098 | | 1.6639 | 4.0 | 92 | 2.3388 | 0.2725 | 0.2702 | 0.2714 | | 1.3815 | 5.0 | 115 | 2.3873 | 0.2710 | 0.2714 | 0.2712 | | 1.1561 | 6.0 | 138 | 2.3997 | 0.2922 | 0.2918 | 0.2920 | | 0.9378 | 7.0 | 161 | 2.4841 | 0.3049 | 0.3078 | 0.3064 | | 0.7814 | 8.0 | 184 | 2.5902 | 0.2925 | 0.2950 | 0.2938 | ### Framework versions - Transformers 4.50.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.21.1