--- library_name: transformers language: - en base_model: Hartunka/tiny_bert_rand_100_v2 tags: - generated_from_trainer datasets: - glue metrics: - spearmanr model-index: - name: tiny_bert_rand_100_v2_stsb results: - task: name: Text Classification type: text-classification dataset: name: GLUE STSB type: glue args: stsb metrics: - name: Spearmanr type: spearmanr value: 0.17464416855612533 --- # tiny_bert_rand_100_v2_stsb This model is a fine-tuned version of [Hartunka/tiny_bert_rand_100_v2](https://huggingface.co/Hartunka/tiny_bert_rand_100_v2) on the GLUE STSB dataset. It achieves the following results on the evaluation set: - Loss: 2.3571 - Pearson: 0.1904 - Spearmanr: 0.1746 - Combined Score: 0.1825 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| | 3.0934 | 1.0 | 23 | 2.4179 | 0.1274 | 0.1252 | 0.1263 | | 2.0262 | 2.0 | 46 | 2.8227 | 0.0906 | 0.0700 | 0.0803 | | 1.8632 | 3.0 | 69 | 2.3571 | 0.1904 | 0.1746 | 0.1825 | | 1.6504 | 4.0 | 92 | 2.4674 | 0.2405 | 0.2359 | 0.2382 | | 1.376 | 5.0 | 115 | 2.4109 | 0.2443 | 0.2405 | 0.2424 | | 1.1686 | 6.0 | 138 | 2.5538 | 0.2573 | 0.2599 | 0.2586 | | 0.9782 | 7.0 | 161 | 2.6227 | 0.2622 | 0.2656 | 0.2639 | | 0.8135 | 8.0 | 184 | 3.0193 | 0.2305 | 0.2377 | 0.2341 | ### Framework versions - Transformers 4.50.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.21.1