| | --- |
| | language: |
| | - en |
| | base_model: Hartunka/tiny_bert_rand_100_v1 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - spearmanr |
| | model-index: |
| | - name: tiny_bert_rand_100_v1_stsb |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE STSB |
| | type: glue |
| | args: stsb |
| | metrics: |
| | - name: Spearmanr |
| | type: spearmanr |
| | value: 0.2763743043991294 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # tiny_bert_rand_100_v1_stsb |
| | |
| | This model is a fine-tuned version of [Hartunka/tiny_bert_rand_100_v1](https://huggingface.co/Hartunka/tiny_bert_rand_100_v1) on the GLUE STSB dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.2768 |
| | - Pearson: 0.2798 |
| | - Spearmanr: 0.2764 |
| | - Combined Score: 0.2781 |
| | |
| | ## 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 | Pearson | Spearmanr | Combined Score | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
| | | 3.4483 | 1.0 | 23 | 2.3146 | 0.1677 | 0.1464 | 0.1571 | |
| | | 2.0255 | 2.0 | 46 | 2.5450 | 0.1168 | 0.1085 | 0.1126 | |
| | | 1.8523 | 3.0 | 69 | 2.3148 | 0.2202 | 0.2082 | 0.2142 | |
| | | 1.6156 | 4.0 | 92 | 2.3427 | 0.2703 | 0.2679 | 0.2691 | |
| | | 1.3454 | 5.0 | 115 | 2.2768 | 0.2798 | 0.2764 | 0.2781 | |
| | | 1.1616 | 6.0 | 138 | 2.6384 | 0.2686 | 0.2783 | 0.2734 | |
| | | 0.9734 | 7.0 | 161 | 2.4772 | 0.2823 | 0.2840 | 0.2831 | |
| | | 0.8406 | 8.0 | 184 | 2.8826 | 0.2435 | 0.2540 | 0.2487 | |
| | | 0.7077 | 9.0 | 207 | 2.9091 | 0.2461 | 0.2524 | 0.2493 | |
| | | 0.6149 | 10.0 | 230 | 2.8235 | 0.2652 | 0.2718 | 0.2685 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.0 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.5.0 |
| | - Tokenizers 0.19.1 |
| | |
