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--- |
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library_name: transformers |
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license: mit |
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base_model: jhu-clsp/mmBERT-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: ftm-zone-classifier |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ftm-zone-classifier |
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This model is a fine-tuned version of [jhu-clsp/mmBERT-base](https://huggingface.co/jhu-clsp/mmBERT-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6612 |
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- Precision: 0.7275 |
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- Recall: 0.7115 |
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- F1: 0.7194 |
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- Accuracy: 0.8238 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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- label_smoothing_factor: 0.05 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.6579 | 1.0 | 342 | 0.6704 | 0.6634 | 0.7273 | 0.6939 | 0.8184 | |
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| 0.6339 | 2.0 | 684 | 0.6612 | 0.7275 | 0.7115 | 0.7194 | 0.8238 | |
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| 0.6074 | 3.0 | 1026 | 0.6346 | 0.6937 | 0.7209 | 0.7071 | 0.8255 | |
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### Framework versions |
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- Transformers 4.57.3 |
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- Pytorch 2.9.1+cu128 |
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- Datasets 4.4.2 |
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- Tokenizers 0.22.2 |
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