| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | license: apache-2.0 |
| | base_model: gokulsrinivasagan/tinybert_base_train_kd |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: tinybert_base_train_kd_mnli |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE MNLI |
| | type: glue |
| | args: mnli |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.7617982099267697 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # tinybert_base_train_kd_mnli |
| |
|
| | This model is a fine-tuned version of [gokulsrinivasagan/tinybert_base_train_kd](https://huggingface.co/gokulsrinivasagan/tinybert_base_train_kd) on the GLUE MNLI dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5858 |
| | - Accuracy: 0.7618 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | | 0.8098 | 1.0 | 1534 | 0.7137 | 0.6905 | |
| | | 0.6666 | 2.0 | 3068 | 0.6576 | 0.7277 | |
| | | 0.5873 | 3.0 | 4602 | 0.6274 | 0.7377 | |
| | | 0.522 | 4.0 | 6136 | 0.6076 | 0.7493 | |
| | | 0.4623 | 5.0 | 7670 | 0.6133 | 0.7570 | |
| | | 0.4069 | 6.0 | 9204 | 0.6448 | 0.7575 | |
| | | 0.3547 | 7.0 | 10738 | 0.6818 | 0.7606 | |
| | | 0.3073 | 8.0 | 12272 | 0.7034 | 0.7603 | |
| | | 0.2658 | 9.0 | 13806 | 0.8077 | 0.7490 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.51.2 |
| | - Pytorch 2.6.0+cu126 |
| | - Datasets 3.5.0 |
| | - Tokenizers 0.21.1 |
| |
|
