| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/bert_base_km_100_v1 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: bert_base_km_100_v1_mnli |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE MNLI |
| | type: glue |
| | args: mnli |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.6495117982099268 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # bert_base_km_100_v1_mnli |
| | |
| | This model is a fine-tuned version of [Hartunka/bert_base_km_100_v1](https://huggingface.co/Hartunka/bert_base_km_100_v1) on the GLUE MNLI dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.8067 |
| | - Accuracy: 0.6495 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | | 0.9905 | 1.0 | 1534 | 0.9129 | 0.5679 | |
| | | 0.8746 | 2.0 | 3068 | 0.8564 | 0.6137 | |
| | | 0.788 | 3.0 | 4602 | 0.8095 | 0.6408 | |
| | | 0.7016 | 4.0 | 6136 | 0.8234 | 0.6445 | |
| | | 0.6148 | 5.0 | 7670 | 0.8329 | 0.6544 | |
| | | 0.5236 | 6.0 | 9204 | 0.9532 | 0.6469 | |
| | | 0.4384 | 7.0 | 10738 | 0.9941 | 0.6431 | |
| | | 0.3583 | 8.0 | 12272 | 1.1222 | 0.6404 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
