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