| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/bert_base_km_10_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: bert_base_km_10_v2_rte |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE RTE |
| | type: glue |
| | args: rte |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.5234657039711191 |
| | --- |
| | |
| | <!-- 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_10_v2_rte |
| | |
| | This model is a fine-tuned version of [Hartunka/bert_base_km_10_v2](https://huggingface.co/Hartunka/bert_base_km_10_v2) on the GLUE RTE dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7182 |
| | - Accuracy: 0.5235 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.7122 | 1.0 | 10 | 0.7220 | 0.5054 | |
| | | 0.6651 | 2.0 | 20 | 0.7182 | 0.5235 | |
| | | 0.6283 | 3.0 | 30 | 0.7291 | 0.5523 | |
| | | 0.558 | 4.0 | 40 | 0.7983 | 0.5126 | |
| | | 0.4573 | 5.0 | 50 | 0.8778 | 0.5343 | |
| | | 0.3427 | 6.0 | 60 | 1.0947 | 0.5054 | |
| | | 0.2296 | 7.0 | 70 | 1.2676 | 0.5162 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| | |
