| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | base_model: Hartunka/distilbert_rand_100_v2 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: distilbert_rand_100_v2_mrpc |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: GLUE MRPC |
| | type: glue |
| | args: mrpc |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.6936274509803921 |
| | - name: F1 |
| | type: f1 |
| | value: 0.7974068071312804 |
| | --- |
| | |
| | <!-- 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_rand_100_v2_mrpc |
| |
|
| | This model is a fine-tuned version of [Hartunka/distilbert_rand_100_v2](https://huggingface.co/Hartunka/distilbert_rand_100_v2) on the GLUE MRPC dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5903 |
| | - Accuracy: 0.6936 |
| | - F1: 0.7974 |
| | - Combined Score: 0.7455 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:| |
| | | 0.6269 | 1.0 | 15 | 0.6202 | 0.6716 | 0.7752 | 0.7234 | |
| | | 0.5818 | 2.0 | 30 | 0.5903 | 0.6936 | 0.7974 | 0.7455 | |
| | | 0.5151 | 3.0 | 45 | 0.6081 | 0.6887 | 0.7928 | 0.7408 | |
| | | 0.412 | 4.0 | 60 | 0.7463 | 0.6446 | 0.7259 | 0.6853 | |
| | | 0.2566 | 5.0 | 75 | 1.0279 | 0.6373 | 0.7197 | 0.6785 | |
| | | 0.1435 | 6.0 | 90 | 1.2920 | 0.6495 | 0.7327 | 0.6911 | |
| | | 0.0905 | 7.0 | 105 | 1.4994 | 0.6324 | 0.7082 | 0.6703 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.50.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.21.1 |
| |
|
