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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: interview_classifier |
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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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# interview_classifier |
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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: 0.5597 |
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- Accuracy: 0.9630 |
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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: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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: 18 |
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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 | 54 | 2.2273 | 0.2130 | |
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| No log | 2.0 | 108 | 2.1305 | 0.3148 | |
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| No log | 3.0 | 162 | 1.9882 | 0.6204 | |
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| No log | 4.0 | 216 | 1.8126 | 0.6852 | |
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| No log | 5.0 | 270 | 1.6344 | 0.7593 | |
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| No log | 6.0 | 324 | 1.4635 | 0.8241 | |
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| No log | 7.0 | 378 | 1.3043 | 0.8426 | |
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| No log | 8.0 | 432 | 1.1541 | 0.8796 | |
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| No log | 9.0 | 486 | 1.0312 | 0.8889 | |
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| 1.7754 | 10.0 | 540 | 0.9199 | 0.9074 | |
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| 1.7754 | 11.0 | 594 | 0.8311 | 0.9259 | |
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| 1.7754 | 12.0 | 648 | 0.7500 | 0.9259 | |
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| 1.7754 | 13.0 | 702 | 0.6884 | 0.9444 | |
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| 1.7754 | 14.0 | 756 | 0.6391 | 0.9444 | |
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| 1.7754 | 15.0 | 810 | 0.6049 | 0.9537 | |
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| 1.7754 | 16.0 | 864 | 0.5796 | 0.9537 | |
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| 1.7754 | 17.0 | 918 | 0.5652 | 0.9630 | |
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| 1.7754 | 18.0 | 972 | 0.5597 | 0.9630 | |
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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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