| --- |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: results_classification |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # results_classification |
| |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2517 |
| - Accuracy: 0.9214 |
| - F1: 0.9214 |
| |
| ## 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: 32 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 50 |
| - training_steps: 500 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
| | 0.152 | 0.0133 | 50 | 0.3216 | 0.9037 | 0.9033 | |
| | 0.1533 | 0.0267 | 100 | 0.3024 | 0.9096 | 0.9095 | |
| | 0.1443 | 0.04 | 150 | 0.3356 | 0.9017 | 0.9010 | |
| | 0.1101 | 0.0533 | 200 | 0.3121 | 0.9134 | 0.9133 | |
| | 0.1147 | 0.0667 | 250 | 0.3813 | 0.9005 | 0.9002 | |
| | 0.1611 | 0.08 | 300 | 0.2992 | 0.9134 | 0.9129 | |
| | 0.1553 | 0.0933 | 350 | 0.2858 | 0.9166 | 0.9166 | |
| | 0.1268 | 0.1067 | 400 | 0.2769 | 0.9186 | 0.9185 | |
| | 0.2011 | 0.12 | 450 | 0.2525 | 0.9214 | 0.9215 | |
| | 0.1845 | 0.1333 | 500 | 0.2517 | 0.9214 | 0.9214 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.41.2 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
|
|
