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---
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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-small-spm
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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-small-spm
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This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5919
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- Accuracy: 0.5095
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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: 0.0001
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- train_batch_size: 256
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 3
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- total_train_batch_size: 768
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- total_eval_batch_size: 24
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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: 0.01
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- num_epochs: 14
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- mixed_precision_training: Native AMP
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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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| 3.3946 | 1.0 | 69473 | 3.2473 | 0.4299 |
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| 3.1526 | 2.0 | 138946 | 2.9987 | 0.4583 |
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| 3.0496 | 3.0 | 208419 | 2.8875 | 0.4715 |
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| 2.9923 | 4.0 | 277892 | 2.8258 | 0.4788 |
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| 2.9429 | 5.0 | 347365 | 2.7765 | 0.4849 |
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| 2.912 | 6.0 | 416838 | 2.7482 | 0.4890 |
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| 2.8813 | 7.0 | 486311 | 2.7103 | 0.4938 |
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| 2.8609 | 8.0 | 555784 | 2.6881 | 0.4963 |
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| 2.8352 | 9.0 | 625257 | 2.6702 | 0.4991 |
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| 2.8163 | 10.0 | 694730 | 2.6510 | 0.5010 |
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| 2.8026 | 11.0 | 764203 | 2.6246 | 0.5046 |
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| 2.7894 | 12.0 | 833676 | 2.6172 | 0.5055 |
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| 2.7728 | 13.0 | 903149 | 2.5994 | 0.5083 |
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| 2.761 | 14.0 | 972622 | 2.5919 | 0.5095 |
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### Framework versions
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- Transformers 4.19.2
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- Pytorch 1.12.0+cu116
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- Datasets 2.2.2
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- Tokenizers 0.12.1
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