Completed Filter Training With Correct Test Set

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/deberta-v3-small
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- recall
+- precision
+model-index:
+- name: PII-Binary-Filter-Extreme-Recall-Fix
+  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. -->
+
+# PII-Binary-Filter-Extreme-Recall-Fix
+
+This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.1566
+- F1: 0.0678
+- Recall: 1.0
+- Precision: 0.0351
+- Trash Caught: 0.2431
+
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 32
+- 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Recall | Precision | Trash Caught |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------------:|
+| 0.2949        | 1.0   | 665  | 3.4996          | 0.0522 | 1.0    | 0.0268    | 0.0          |
+| 0.1957        | 2.0   | 1330 | 2.6878          | 0.0602 | 0.8333 | 0.0312    | 0.2890       |
+| 0.1554        | 3.0   | 1995 | 3.1566          | 0.0678 | 1.0    | 0.0351    | 0.2431       |
+
+
+### Framework versions
+
+- Transformers 4.56.0
+- Pytorch 2.8.0+cu129
+- Datasets 4.8.2
+- Tokenizers 0.22.0

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