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End of training

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README.md ADDED
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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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+
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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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+
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+ # ftm-zone-classifier
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+
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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: 0.4286
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+ - Precision: 0.5653
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+ - Recall: 0.6937
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+ - F1: 0.6230
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+ - Accuracy: 0.7088
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 16
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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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: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.4279 | 1.0 | 486 | 0.4582 | 0.5508 | 0.6867 | 0.6112 | 0.6967 |
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+ | 0.4106 | 2.0 | 972 | 0.4288 | 0.5141 | 0.7058 | 0.5949 | 0.6640 |
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+ | 0.4069 | 3.0 | 1458 | 0.4286 | 0.5653 | 0.6937 | 0.6230 | 0.7088 |
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+ | 0.3529 | 4.0 | 1944 | 0.4346 | 0.5228 | 0.6986 | 0.5981 | 0.7192 |
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+ | 0.3341 | 5.0 | 2430 | 0.4613 | 0.5283 | 0.6915 | 0.5990 | 0.7192 |
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+
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+
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+ ### Framework versions
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+
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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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