| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert/distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: ATSC |
| 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. --> |
|
|
| # ATSC |
|
|
| 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: 0.9021 |
| - Accuracy: 0.6497 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - 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: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.9519 | 1.0 | 113 | 0.9002 | 0.6497 | |
| | 0.9445 | 2.0 | 226 | 0.9034 | 0.6497 | |
| | 0.9412 | 3.0 | 339 | 0.8924 | 0.6497 | |
| | 0.9388 | 4.0 | 452 | 0.8920 | 0.6497 | |
| | 0.9369 | 5.0 | 565 | 0.8950 | 0.6497 | |
| | 0.9359 | 6.0 | 678 | 0.8957 | 0.6497 | |
| | 0.9327 | 7.0 | 791 | 0.8976 | 0.6497 | |
| | 0.9338 | 8.0 | 904 | 0.9006 | 0.6497 | |
| | 0.9312 | 9.0 | 1017 | 0.9013 | 0.6497 | |
| | 0.9317 | 10.0 | 1130 | 0.9021 | 0.6497 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.47.0 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
|
|
