| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: bert-base-cased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: AMANDA |
| | 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. --> |
| |
|
| | # AMANDA |
| |
|
| | This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4717 |
| | - Accuracy: 0.8243 |
| |
|
| | ## 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: 16 |
| | - 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 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 1.2389 | 0.0769 | 5 | 0.8651 | 0.8243 | |
| | | 0.6616 | 0.1538 | 10 | 0.6137 | 0.8243 | |
| | | 0.3941 | 0.2308 | 15 | 0.6143 | 0.8243 | |
| | | 0.6576 | 0.3077 | 20 | 0.5270 | 0.8243 | |
| | | 0.4628 | 0.3846 | 25 | 0.4904 | 0.8243 | |
| | | 0.4493 | 0.4615 | 30 | 0.5351 | 0.8243 | |
| | | 0.5603 | 0.5385 | 35 | 0.5049 | 0.8243 | |
| | | 0.5586 | 0.6154 | 40 | 0.4949 | 0.8243 | |
| | | 0.528 | 0.6923 | 45 | 0.4784 | 0.8243 | |
| | | 0.6357 | 0.7692 | 50 | 0.4717 | 0.8243 | |
| | | 0.4228 | 0.8462 | 55 | 0.4674 | 0.8243 | |
| | | 0.4739 | 0.9231 | 60 | 0.4616 | 0.8243 | |
| | | 0.4855 | 1.0 | 65 | 0.4503 | 0.8243 | |
| | | 0.6234 | 1.0769 | 70 | 0.4921 | 0.8243 | |
| | | 0.5158 | 1.1538 | 75 | 0.4351 | 0.8243 | |
| | | 0.3356 | 1.2308 | 80 | 0.4576 | 0.8243 | |
| | | 0.4118 | 1.3077 | 85 | 0.4457 | 0.8243 | |
| | | 0.39 | 1.3846 | 90 | 0.4153 | 0.8243 | |
| | | 0.3848 | 1.4615 | 95 | 0.4377 | 0.8243 | |
| | | 0.3499 | 1.5385 | 100 | 0.4427 | 0.8209 | |
| | | 0.3776 | 1.6154 | 105 | 0.3825 | 0.8446 | |
| | | 0.4228 | 1.6923 | 110 | 0.3755 | 0.8345 | |
| | | 0.3157 | 1.7692 | 115 | 0.4031 | 0.8243 | |
| | | 0.3163 | 1.8462 | 120 | 0.4938 | 0.8277 | |
| | | 0.504 | 1.9231 | 125 | 0.4861 | 0.8277 | |
| | | 0.4722 | 2.0 | 130 | 0.4717 | 0.8243 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.57.1 |
| | - Pytorch 2.8.0+cu126 |
| | - Datasets 4.4.1 |
| | - Tokenizers 0.22.1 |
| | |
