| | --- |
| | base_model: distilbert/distilbert-base-uncased |
| | library_name: transformers |
| | license: apache-2.0 |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: results |
| | 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 |
| |
|
| | This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3829 |
| | - Accuracy: 0.9002 |
| | - F1: 0.9024 |
| | - Precision: 0.8993 |
| | - Recall: 0.9054 |
| |
|
| | ## 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: 16 |
| | - 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: 500 |
| | - num_epochs: 3 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | | 0.1293 | 1.0 | 4210 | 0.3084 | 0.8922 | 0.8941 | 0.8941 | 0.8941 | |
| | | 0.0939 | 2.0 | 8420 | 0.3646 | 0.8933 | 0.9001 | 0.8604 | 0.9437 | |
| | | 0.0981 | 3.0 | 12630 | 0.3829 | 0.9002 | 0.9024 | 0.8993 | 0.9054 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.45.2 |
| | - Pytorch 2.5.0+cu124 |
| | - Datasets 3.0.1 |
| | - Tokenizers 0.20.1 |
| | |
