| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: distilbert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: my_awesome_qa_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. --> |
| |
|
| | # my_awesome_qa_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: 1.5971 |
| | |
| | ## 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: 2e-05 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.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 | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | No log | 1.0 | 63 | 3.4355 | |
| | | No log | 2.0 | 126 | 2.6230 | |
| | | No log | 3.0 | 189 | 1.8876 | |
| | | No log | 4.0 | 252 | 1.6358 | |
| | | No log | 5.0 | 315 | 1.5591 | |
| | | No log | 6.0 | 378 | 1.5578 | |
| | | No log | 7.0 | 441 | 1.5629 | |
| | | 1.9367 | 8.0 | 504 | 1.5743 | |
| | | 1.9367 | 9.0 | 567 | 1.5862 | |
| | | 1.9367 | 10.0 | 630 | 1.5971 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.47.1 |
| | - Pytorch 2.5.1+cu124 |
| | - Datasets 3.2.0 |
| | - Tokenizers 0.21.0 |
| | |
