| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/distilbert_km_50_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: distilbert_km_50_v2_mrpc |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE MRPC |
| | type: glue |
| | args: mrpc |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.7009803921568627 |
| | - name: F1 |
| | type: f1 |
| | value: 0.8145896656534954 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # distilbert_km_50_v2_mrpc |
| |
|
| | This model is a fine-tuned version of [Hartunka/distilbert_km_50_v2](https://huggingface.co/Hartunka/distilbert_km_50_v2) on the GLUE MRPC dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5974 |
| | - Accuracy: 0.7010 |
| | - F1: 0.8146 |
| | - Combined Score: 0.7578 |
| |
|
| | ## 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 | F1 | Combined Score | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:| |
| | | 0.6312 | 1.0 | 15 | 0.6016 | 0.7010 | 0.8152 | 0.7581 | |
| | | 0.5856 | 2.0 | 30 | 0.5974 | 0.7010 | 0.8146 | 0.7578 | |
| | | 0.5365 | 3.0 | 45 | 0.6001 | 0.7083 | 0.8161 | 0.7622 | |
| | | 0.4884 | 4.0 | 60 | 0.6060 | 0.6961 | 0.7954 | 0.7457 | |
| | | 0.4025 | 5.0 | 75 | 0.6637 | 0.6765 | 0.7692 | 0.7229 | |
| | | 0.3023 | 6.0 | 90 | 0.7732 | 0.6667 | 0.7580 | 0.7123 | |
| | | 0.1918 | 7.0 | 105 | 0.9304 | 0.6569 | 0.7552 | 0.7061 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| |
|
