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update model card README.md
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README.md
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---
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license: apache-2.0
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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: bert-base-cased-cv-studio_name-medium
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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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# bert-base-cased-cv-studio_name-medium
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.3310
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- Accuracy: 0.6388
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- F1 Micro: 0.6388
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- F1 Macro: 0.5001
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- Precision Micro: 0.6388
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- Recall Micro: 0.6388
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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: 16
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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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- lr_scheduler_warmup_steps: 20
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Micro | F1 Macro | Precision Micro | Recall Micro |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:--------:|:---------------:|:------------:|
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| 1.4139 | 0.98 | 1000 | 1.3831 | 0.6039 | 0.6039 | 0.4188 | 0.6039 | 0.6039 |
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| 1.1561 | 1.96 | 2000 | 1.2386 | 0.6554 | 0.6554 | 0.4743 | 0.6554 | 0.6554 |
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| 0.9183 | 2.93 | 3000 | 1.2201 | 0.6576 | 0.6576 | 0.5011 | 0.6576 | 0.6576 |
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| 0.677 | 3.91 | 4000 | 1.3478 | 0.6442 | 0.6442 | 0.5206 | 0.6442 | 0.6442 |
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| 0.4857 | 4.89 | 5000 | 1.4765 | 0.6393 | 0.6393 | 0.5215 | 0.6393 | 0.6393 |
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| 0.3318 | 5.87 | 6000 | 1.6924 | 0.6442 | 0.6442 | 0.5024 | 0.6442 | 0.6442 |
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| 0.2273 | 6.84 | 7000 | 1.8645 | 0.6444 | 0.6444 | 0.5060 | 0.6444 | 0.6444 |
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| 0.1396 | 7.82 | 8000 | 2.1143 | 0.6381 | 0.6381 | 0.5181 | 0.6381 | 0.6381 |
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| 0.0841 | 8.8 | 9000 | 2.2699 | 0.6359 | 0.6359 | 0.5065 | 0.6359 | 0.6359 |
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| 0.0598 | 9.78 | 10000 | 2.3310 | 0.6388 | 0.6388 | 0.5001 | 0.6388 | 0.6388 |
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### Framework versions
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- Transformers 4.19.0
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- Pytorch 1.8.2+cu111
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- Datasets 1.6.2
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- Tokenizers 0.12.1
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