| | --- |
| | language: |
| | - en |
| | base_model: Hartunka/tiny_bert_rand_100_v1 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: tiny_bert_rand_100_v1_qnli |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE QNLI |
| | type: glue |
| | args: qnli |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.61925681859784 |
| | --- |
| | |
| | <!-- 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_qnli |
| | |
| | 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 QNLI dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6503 |
| | - Accuracy: 0.6193 |
| | |
| | ## 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 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.6657 | 1.0 | 410 | 0.6503 | 0.6193 | |
| | | 0.6367 | 2.0 | 820 | 0.6539 | 0.6213 | |
| | | 0.5927 | 3.0 | 1230 | 0.6680 | 0.6129 | |
| | | 0.531 | 4.0 | 1640 | 0.7184 | 0.6116 | |
| | | 0.4631 | 5.0 | 2050 | 0.8040 | 0.6059 | |
| | | 0.3972 | 6.0 | 2460 | 0.9131 | 0.6070 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.0 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.5.0 |
| | - Tokenizers 0.19.1 |
| | |
