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README.md

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+---
+base_model: kghanlon/distilbert-base-uncased-finetuned-MP-unannotated-half-frozen-v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- recall
+- f1
+model-index:
+- name: distilbert-base-uncased-finetuned-MP-unannotated-half-frozen-v1-FULL_CLASSES-v1_un_frozen
+  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. -->
+
+# distilbert-base-uncased-finetuned-MP-unannotated-half-frozen-v1-FULL_CLASSES-v1_un_frozen
+
+This model is a fine-tuned version of [kghanlon/distilbert-base-uncased-finetuned-MP-unannotated-half-frozen-v1](https://huggingface.co/kghanlon/distilbert-base-uncased-finetuned-MP-unannotated-half-frozen-v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.2635
+- Accuracy: 0.5909
+- Recall: 0.5909
+- F1: 0.5861
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Recall | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|
+| 1.7051        | 1.0   | 15490 | 1.6329          | 0.5557   | 0.5557 | 0.5381 |
+| 1.3579        | 2.0   | 30980 | 1.5647          | 0.5771   | 0.5771 | 0.5650 |
+| 1.0119        | 3.0   | 46470 | 1.6397          | 0.5900   | 0.5900 | 0.5821 |
+| 0.5922        | 4.0   | 61960 | 1.9336          | 0.5922   | 0.5922 | 0.5855 |
+| 0.3721        | 5.0   | 77450 | 2.2635          | 0.5909   | 0.5909 | 0.5861 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0