| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: customer_support_model |
| 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. --> |
|
|
| # customer_support_model |
|
|
| 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: 0.0004 |
| - Accuracy: 0.9999 |
| - F1 Score: 0.9999 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 2 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
| | 0.0261 | 0.4 | 1000 | 0.0186 | 0.996 | 0.9960 | |
| | 0.0410 | 0.8 | 2000 | 0.0142 | 0.996 | 0.9960 | |
| | 0.0015 | 1.2 | 3000 | 0.0031 | 0.9993 | 0.9993 | |
| | 0.0043 | 1.6 | 4000 | 0.0017 | 0.9997 | 0.9997 | |
| | 0.0004 | 2.0 | 5000 | 0.0004 | 0.9999 | 0.9999 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.12.1 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
