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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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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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- f1 |
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model-index: |
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- name: results_classification |
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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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# results_classification |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2517 |
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- Accuracy: 0.9214 |
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- F1: 0.9214 |
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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: 32 |
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- eval_batch_size: 64 |
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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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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 500 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
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| 0.152 | 0.0133 | 50 | 0.3216 | 0.9037 | 0.9033 | |
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| 0.1533 | 0.0267 | 100 | 0.3024 | 0.9096 | 0.9095 | |
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| 0.1443 | 0.04 | 150 | 0.3356 | 0.9017 | 0.9010 | |
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| 0.1101 | 0.0533 | 200 | 0.3121 | 0.9134 | 0.9133 | |
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| 0.1147 | 0.0667 | 250 | 0.3813 | 0.9005 | 0.9002 | |
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| 0.1611 | 0.08 | 300 | 0.2992 | 0.9134 | 0.9129 | |
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| 0.1553 | 0.0933 | 350 | 0.2858 | 0.9166 | 0.9166 | |
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| 0.1268 | 0.1067 | 400 | 0.2769 | 0.9186 | 0.9185 | |
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| 0.2011 | 0.12 | 450 | 0.2525 | 0.9214 | 0.9215 | |
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| 0.1845 | 0.1333 | 500 | 0.2517 | 0.9214 | 0.9214 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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