| --- |
| library_name: transformers |
| license: mit |
| base_model: jhu-clsp/mmBERT-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: ftm-zone-classifier |
| 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. --> |
|
|
| # ftm-zone-classifier |
|
|
| This model is a fine-tuned version of [jhu-clsp/mmBERT-base](https://huggingface.co/jhu-clsp/mmBERT-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6612 |
| - Precision: 0.7275 |
| - Recall: 0.7115 |
| - F1: 0.7194 |
| - Accuracy: 0.8238 |
|
|
| ## 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: 8 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 64 |
| - 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 |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 3 |
| - label_smoothing_factor: 0.05 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.6579 | 1.0 | 342 | 0.6704 | 0.6634 | 0.7273 | 0.6939 | 0.8184 | |
| | 0.6339 | 2.0 | 684 | 0.6612 | 0.7275 | 0.7115 | 0.7194 | 0.8238 | |
| | 0.6074 | 3.0 | 1026 | 0.6346 | 0.6937 | 0.7209 | 0.7071 | 0.8255 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.3 |
| - Pytorch 2.9.1+cu128 |
| - Datasets 4.4.2 |
| - Tokenizers 0.22.2 |
| |
