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--- |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: distilbert-base-uncased |
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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 |
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0002 |
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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: 2e-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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:-----:|:---------------:| |
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| 0.0273 | 0.2907 | 500 | 0.0062 | |
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| 0.0049 | 0.5814 | 1000 | 0.0024 | |
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| 0.0033 | 0.8721 | 1500 | 0.0020 | |
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| 0.0014 | 1.1628 | 2000 | 0.0009 | |
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| 0.001 | 1.4535 | 2500 | 0.0007 | |
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| 0.0008 | 1.7442 | 3000 | 0.0009 | |
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| 0.0011 | 2.0349 | 3500 | 0.0011 | |
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| 0.0003 | 2.3256 | 4000 | 0.0012 | |
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| 0.0008 | 2.6163 | 4500 | 0.0008 | |
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| 0.0006 | 2.9070 | 5000 | 0.0010 | |
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| 0.0006 | 3.1977 | 5500 | 0.0009 | |
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| 0.0002 | 3.4884 | 6000 | 0.0008 | |
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| 0.0005 | 3.7791 | 6500 | 0.0005 | |
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| 0.0003 | 4.0698 | 7000 | 0.0005 | |
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| 0.0002 | 4.3605 | 7500 | 0.0003 | |
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| 0.0004 | 4.6512 | 8000 | 0.0015 | |
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| 0.0004 | 4.9419 | 8500 | 0.0008 | |
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| 0.0002 | 5.2326 | 9000 | 0.0002 | |
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| 0.0003 | 5.5233 | 9500 | 0.0003 | |
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| 0.0002 | 5.8140 | 10000 | 0.0002 | |
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| 0.0002 | 6.1047 | 10500 | 0.0003 | |
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| 0.0001 | 6.3953 | 11000 | 0.0002 | |
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| 0.0001 | 6.6860 | 11500 | 0.0002 | |
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| 0.0001 | 6.9767 | 12000 | 0.0003 | |
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| 0.0 | 7.2674 | 12500 | 0.0002 | |
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| 0.0 | 7.5581 | 13000 | 0.0009 | |
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| 0.0001 | 7.8488 | 13500 | 0.0005 | |
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| 0.0002 | 8.1395 | 14000 | 0.0007 | |
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| 0.0001 | 8.4302 | 14500 | 0.0007 | |
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| 0.0001 | 8.7209 | 15000 | 0.0006 | |
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| 0.0001 | 9.0116 | 15500 | 0.0005 | |
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| 0.0 | 9.3023 | 16000 | 0.0007 | |
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| 0.0001 | 9.5930 | 16500 | 0.0005 | |
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| 0.0003 | 9.8837 | 17000 | 0.0004 | |
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| 0.0 | 10.1744 | 17500 | 0.0004 | |
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| 0.0002 | 10.4651 | 18000 | 0.0003 | |
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| 0.0 | 10.7558 | 18500 | 0.0003 | |
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| 0.0 | 11.0465 | 19000 | 0.0004 | |
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| 0.0 | 11.3372 | 19500 | 0.0004 | |
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| 0.0 | 11.6279 | 20000 | 0.0002 | |
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| 0.0 | 11.9186 | 20500 | 0.0002 | |
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| 0.0 | 12.2093 | 21000 | 0.0003 | |
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| 0.0 | 12.5 | 21500 | 0.0003 | |
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| 0.0 | 12.7907 | 22000 | 0.0004 | |
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| 0.0 | 13.0814 | 22500 | 0.0002 | |
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| 0.0001 | 13.3721 | 23000 | 0.0002 | |
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| 0.0001 | 13.6628 | 23500 | 0.0002 | |
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| 0.0 | 13.9535 | 24000 | 0.0002 | |
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| 0.0 | 14.2442 | 24500 | 0.0002 | |
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| 0.0 | 14.5349 | 25000 | 0.0002 | |
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| 0.0 | 14.8256 | 25500 | 0.0002 | |
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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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