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--- |
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license: apache-2.0 |
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base_model: bert-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: finetuned_bert-base |
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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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# finetuned_bert-base |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2046 |
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- Accuracy: 0.52 |
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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: 32 |
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- eval_batch_size: 32 |
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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_ratio: 0.1 |
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- num_epochs: 15 |
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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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| 1.413 | 1.0 | 75 | 1.3023 | 0.4667 | |
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| 1.2772 | 2.0 | 150 | 1.2043 | 0.52 | |
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| 1.2019 | 3.0 | 225 | 1.0879 | 0.5733 | |
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| 1.1463 | 4.0 | 300 | 1.1124 | 0.57 | |
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| 1.1566 | 5.0 | 375 | 1.1220 | 0.5367 | |
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| 1.1096 | 6.0 | 450 | 1.0675 | 0.5967 | |
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| 0.9806 | 7.0 | 525 | 1.0315 | 0.64 | |
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| 0.8715 | 8.0 | 600 | 1.0616 | 0.6 | |
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| 0.8788 | 9.0 | 675 | 1.1211 | 0.59 | |
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| 0.8071 | 10.0 | 750 | 1.1400 | 0.6 | |
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| 0.6908 | 11.0 | 825 | 1.1848 | 0.6033 | |
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| 0.6244 | 12.0 | 900 | 1.2255 | 0.59 | |
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| 0.628 | 13.0 | 975 | 1.2264 | 0.6 | |
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| 0.6003 | 14.0 | 1050 | 1.2270 | 0.6033 | |
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| 0.5283 | 15.0 | 1125 | 1.2399 | 0.5933 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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