--- library_name: transformers language: - en base_model: Hartunka/bert_base_rand_100_v2 tags: - generated_from_trainer datasets: - glue metrics: - spearmanr model-index: - name: bert_base_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: 0.21780785979027786 --- # bert_base_rand_100_v2_stsb This model is a fine-tuned version of [Hartunka/bert_base_rand_100_v2](https://huggingface.co/Hartunka/bert_base_rand_100_v2) on the GLUE STSB dataset. It achieves the following results on the evaluation set: - Loss: 2.4307 - Pearson: 0.2244 - Spearmanr: 0.2178 - Combined Score: 0.2211 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| | 2.8477 | 1.0 | 23 | 2.5026 | 0.0881 | 0.0800 | 0.0840 | | 1.9428 | 2.0 | 46 | 2.4721 | 0.1475 | 0.1358 | 0.1417 | | 1.6984 | 3.0 | 69 | 2.4307 | 0.2244 | 0.2178 | 0.2211 | | 1.3566 | 4.0 | 92 | 2.5091 | 0.2426 | 0.2407 | 0.2416 | | 1.0597 | 5.0 | 115 | 2.5674 | 0.2486 | 0.2424 | 0.2455 | | 0.8102 | 6.0 | 138 | 2.6909 | 0.2713 | 0.2666 | 0.2690 | | 0.6127 | 7.0 | 161 | 2.7525 | 0.2639 | 0.2592 | 0.2616 | | 0.4965 | 8.0 | 184 | 2.8618 | 0.2606 | 0.2565 | 0.2586 | ### Framework versions - Transformers 4.50.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.21.1