| --- |
| library_name: transformers |
| language: |
| - en |
| base_model: Hartunka/distilbert_rand_100_v1 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - glue |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: distilbert_rand_100_v1_mrpc |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: GLUE MRPC |
| type: glue |
| args: mrpc |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.6887254901960784 |
| - name: F1 |
| type: f1 |
| value: 0.7954911433172303 |
| --- |
| |
| <!-- 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_v1_mrpc |
|
|
| This model is a fine-tuned version of [Hartunka/distilbert_rand_100_v1](https://huggingface.co/Hartunka/distilbert_rand_100_v1) on the GLUE MRPC dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5919 |
| - Accuracy: 0.6887 |
| - F1: 0.7955 |
| - Combined Score: 0.7421 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:| |
| | 0.6255 | 1.0 | 15 | 0.6193 | 0.6495 | 0.7613 | 0.7054 | |
| | 0.5796 | 2.0 | 30 | 0.5919 | 0.6887 | 0.7955 | 0.7421 | |
| | 0.5137 | 3.0 | 45 | 0.6295 | 0.6716 | 0.7846 | 0.7281 | |
| | 0.4067 | 4.0 | 60 | 0.7786 | 0.625 | 0.7052 | 0.6651 | |
| | 0.2548 | 5.0 | 75 | 1.0054 | 0.6446 | 0.7349 | 0.6898 | |
| | 0.1579 | 6.0 | 90 | 1.3867 | 0.6225 | 0.7220 | 0.6723 | |
| | 0.1051 | 7.0 | 105 | 1.4424 | 0.6078 | 0.6958 | 0.6518 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.50.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.21.1 |
|
|
