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--- |
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license: apache-2.0 |
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base_model: bert-large-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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: output |
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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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# output |
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8310 |
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- Accuracy: 0.7919 |
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- Precision: 0.8030 |
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- Recall: 0.7919 |
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- F1: 0.7889 |
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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: 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: 12 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 495 | 1.0327 | 0.7253 | 0.7362 | 0.7253 | 0.7090 | |
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| 1.68 | 2.0 | 990 | 0.8310 | 0.7919 | 0.8030 | 0.7919 | 0.7889 | |
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| 0.8242 | 3.0 | 1485 | 0.8599 | 0.8091 | 0.8106 | 0.8091 | 0.8013 | |
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| 0.6748 | 4.0 | 1980 | 0.8628 | 0.8263 | 0.8125 | 0.8263 | 0.8158 | |
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| 0.4822 | 5.0 | 2475 | 1.0139 | 0.8162 | 0.8065 | 0.8162 | 0.8070 | |
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| 0.3781 | 6.0 | 2970 | 1.0535 | 0.8081 | 0.8013 | 0.8081 | 0.8011 | |
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| 0.3832 | 7.0 | 3465 | 1.1459 | 0.8081 | 0.8039 | 0.8081 | 0.8034 | |
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| 0.3101 | 8.0 | 3960 | 1.3831 | 0.7788 | 0.8079 | 0.7788 | 0.7847 | |
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| 0.2665 | 9.0 | 4455 | 1.2051 | 0.8222 | 0.8263 | 0.8222 | 0.8197 | |
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| 0.2286 | 10.0 | 4950 | 1.4487 | 0.7980 | 0.8064 | 0.7980 | 0.7962 | |
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| 0.2163 | 11.0 | 5445 | 1.4848 | 0.8121 | 0.8240 | 0.8121 | 0.8123 | |
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| 0.1965 | 12.0 | 5940 | 1.4572 | 0.7919 | 0.8051 | 0.7919 | 0.7919 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Tokenizers 0.15.0 |
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