| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/tiny_bert_km_5_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: tiny_bert_km_5_v2_mnli |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE MNLI |
| | type: glue |
| | args: mnli |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.6934499593165175 |
| | --- |
| | |
| | <!-- 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_km_5_v2_mnli |
| | |
| | This model is a fine-tuned version of [Hartunka/tiny_bert_km_5_v2](https://huggingface.co/Hartunka/tiny_bert_km_5_v2) on the GLUE MNLI dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7252 |
| | - Accuracy: 0.6934 |
| | |
| | ## 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 | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | | 0.9851 | 1.0 | 1534 | 0.8962 | 0.5840 | |
| | | 0.8564 | 2.0 | 3068 | 0.8021 | 0.6428 | |
| | | 0.7776 | 3.0 | 4602 | 0.7621 | 0.6653 | |
| | | 0.7255 | 4.0 | 6136 | 0.7469 | 0.6748 | |
| | | 0.6815 | 5.0 | 7670 | 0.7374 | 0.6852 | |
| | | 0.6403 | 6.0 | 9204 | 0.7440 | 0.6904 | |
| | | 0.6029 | 7.0 | 10738 | 0.7365 | 0.6919 | |
| | | 0.5657 | 8.0 | 12272 | 0.7683 | 0.6909 | |
| | | 0.5311 | 9.0 | 13806 | 0.8053 | 0.6910 | |
| | | 0.4934 | 10.0 | 15340 | 0.8146 | 0.6928 | |
| | | 0.4595 | 11.0 | 16874 | 0.8573 | 0.6912 | |
| | | 0.4278 | 12.0 | 18408 | 0.8758 | 0.6904 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
