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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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model-index: |
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- name: semantic-bert-balanced-dataset |
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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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# semantic-bert-balanced-dataset |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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: 3.1862 |
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- Accuracy: 0.5448 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 160 | 0.8837 | 0.5746 | |
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| No log | 2.0 | 320 | 0.9415 | 0.5490 | |
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| No log | 3.0 | 480 | 1.0334 | 0.5669 | |
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| 0.7136 | 4.0 | 640 | 1.1917 | 0.5661 | |
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| 0.7136 | 5.0 | 800 | 1.3571 | 0.5780 | |
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| 0.7136 | 6.0 | 960 | 1.6461 | 0.5772 | |
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| 0.2277 | 7.0 | 1120 | 2.1103 | 0.5533 | |
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| 0.2277 | 8.0 | 1280 | 2.3829 | 0.5584 | |
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| 0.2277 | 9.0 | 1440 | 2.4821 | 0.5618 | |
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| 0.0617 | 10.0 | 1600 | 2.7549 | 0.5371 | |
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| 0.0617 | 11.0 | 1760 | 2.8267 | 0.5499 | |
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| 0.0617 | 12.0 | 1920 | 2.9028 | 0.5490 | |
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| 0.0242 | 13.0 | 2080 | 2.9845 | 0.5465 | |
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| 0.0242 | 14.0 | 2240 | 3.0126 | 0.5541 | |
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| 0.0242 | 15.0 | 2400 | 3.0791 | 0.5490 | |
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| 0.0086 | 16.0 | 2560 | 3.0980 | 0.5499 | |
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| 0.0086 | 17.0 | 2720 | 3.1564 | 0.5456 | |
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| 0.0086 | 18.0 | 2880 | 3.1723 | 0.5499 | |
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| 0.0048 | 19.0 | 3040 | 3.1791 | 0.5473 | |
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| 0.0048 | 20.0 | 3200 | 3.1862 | 0.5448 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.3.0.dev20231224 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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