| | --- |
| | base_model: distilbert/distilbert-base-uncased |
| | library_name: peft |
| | license: apache-2.0 |
| | metrics: |
| | - accuracy |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: news-category-classifier-distilbert |
| | 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. --> |
| |
|
| | # news-category-classifier-distilbert |
| |
|
| | This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1640 |
| | - Accuracy: 0.9474 |
| |
|
| | ## 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: 0.0002 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 128 |
| | - 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: 10 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Accuracy | Validation Loss | |
| | |:-------------:|:-----:|:-----:|:--------:|:---------------:| |
| | | 0.3293 | 1.0 | 2289 | 0.9119 | 0.2599 | |
| | | 0.0576 | 2.0 | 4578 | 0.9193 | 0.2425 | |
| | | 0.4575 | 3.0 | 6867 | 0.9223 | 0.2401 | |
| | | 0.0339 | 4.0 | 9156 | 0.9245 | 0.2353 | |
| | | 0.0512 | 5.0 | 11445 | 0.9267 | 0.2367 | |
| | | 0.3254 | 6.0 | 13734 | 0.9267 | 0.2367 | |
| | | 0.5933 | 7.0 | 16023 | 0.9482 | 0.1654 | |
| | | 0.136 | 8.0 | 18312 | 0.9482 | 0.1654 | |
| | | 0.3128 | 9.0 | 20601 | 0.1640 | 0.9474 | |
| | | 0.0458 | 10.0 | 22890 | 0.1640 | 0.9474 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.12.0 |
| | - Transformers 4.42.3 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
