| --- |
| language: |
| - en |
| base_model: Hartunka/tiny_bert_rand_50_v1 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - glue |
| metrics: |
| - accuracy |
| model-index: |
| - name: tiny_bert_rand_50_v1_mnli |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: GLUE MNLI |
| type: glue |
| args: mnli |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.6044548413344182 |
| --- |
| |
| <!-- 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_50_v1_mnli |
| |
| This model is a fine-tuned version of [Hartunka/tiny_bert_rand_50_v1](https://huggingface.co/Hartunka/tiny_bert_rand_50_v1) on the GLUE MNLI dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8632 |
| - Accuracy: 0.6045 |
| |
| ## 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.9908 | 1.0 | 1534 | 0.9352 | 0.5470 | |
| | 0.9036 | 2.0 | 3068 | 0.8886 | 0.5874 | |
| | 0.8527 | 3.0 | 4602 | 0.8672 | 0.6013 | |
| | 0.8101 | 4.0 | 6136 | 0.8601 | 0.6128 | |
| | 0.7693 | 5.0 | 7670 | 0.8588 | 0.6098 | |
| | 0.7296 | 6.0 | 9204 | 0.8737 | 0.6214 | |
| | 0.6889 | 7.0 | 10738 | 0.8843 | 0.6221 | |
| | 0.6504 | 8.0 | 12272 | 0.9532 | 0.6102 | |
| | 0.6127 | 9.0 | 13806 | 0.9572 | 0.6201 | |
| | 0.5741 | 10.0 | 15340 | 0.9934 | 0.6180 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.5.0 |
| - Tokenizers 0.19.1 |
| |
