---
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