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--- |
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license: mit |
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base_model: prajjwal1/bert-tiny |
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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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- f1 |
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model-index: |
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- name: MM-MM03 |
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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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# MM-MM03 |
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This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6872 |
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- Accuracy: 0.57 |
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- F1: 0.5203 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| No log | 0.0 | 50 | 0.6915 | 0.53 | 0.3672 | |
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| No log | 0.01 | 100 | 0.6923 | 0.53 | 0.3672 | |
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| No log | 0.01 | 150 | 0.6919 | 0.53 | 0.3672 | |
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| No log | 0.01 | 200 | 0.6923 | 0.54 | 0.4195 | |
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| No log | 0.02 | 250 | 0.6924 | 0.6 | 0.5777 | |
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| No log | 0.02 | 300 | 0.6908 | 0.54 | 0.3892 | |
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| No log | 0.03 | 350 | 0.6893 | 0.55 | 0.4104 | |
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| No log | 0.03 | 400 | 0.6911 | 0.57 | 0.5437 | |
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| No log | 0.03 | 450 | 0.6904 | 0.57 | 0.5482 | |
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| 0.6938 | 0.04 | 500 | 0.6981 | 0.47 | 0.3005 | |
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| 0.6938 | 0.04 | 550 | 0.6953 | 0.47 | 0.3005 | |
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| 0.6938 | 0.04 | 600 | 0.6891 | 0.56 | 0.5252 | |
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| 0.6938 | 0.05 | 650 | 0.6871 | 0.55 | 0.4817 | |
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| 0.6938 | 0.05 | 700 | 0.6898 | 0.56 | 0.4975 | |
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| 0.6938 | 0.06 | 750 | 0.6899 | 0.55 | 0.4817 | |
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| 0.6938 | 0.06 | 800 | 0.6906 | 0.51 | 0.5102 | |
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| 0.6938 | 0.06 | 850 | 0.6934 | 0.48 | 0.48 | |
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| 0.6938 | 0.07 | 900 | 0.6889 | 0.55 | 0.4817 | |
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| 0.6938 | 0.07 | 950 | 0.6996 | 0.47 | 0.3175 | |
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| 0.6929 | 0.07 | 1000 | 0.6894 | 0.59 | 0.5601 | |
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| 0.6929 | 0.08 | 1050 | 0.6941 | 0.5 | 0.4777 | |
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| 0.6929 | 0.08 | 1100 | 0.6927 | 0.49 | 0.4896 | |
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| 0.6929 | 0.08 | 1150 | 0.6916 | 0.49 | 0.4903 | |
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| 0.6929 | 0.09 | 1200 | 0.6874 | 0.56 | 0.5252 | |
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| 0.6929 | 0.09 | 1250 | 0.6872 | 0.57 | 0.5203 | |
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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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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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