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--- |
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base_model: MiMe-MeMo/MeMo-BERT-01 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: MeMo_BERT-SA_1 |
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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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# MeMo_BERT-SA_1 |
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This model is a fine-tuned version of [MiMe-MeMo/MeMo-BERT-01](https://huggingface.co/MiMe-MeMo/MeMo-BERT-01) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7236 |
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- F1-score: 0.5887 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1-score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 265 | 1.0173 | 0.4110 | |
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| 0.9885 | 2.0 | 530 | 0.9694 | 0.5053 | |
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| 0.9885 | 3.0 | 795 | 1.1486 | 0.4695 | |
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| 0.7354 | 4.0 | 1060 | 1.1729 | 0.5363 | |
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| 0.7354 | 5.0 | 1325 | 1.2851 | 0.5822 | |
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| 0.4299 | 6.0 | 1590 | 1.7236 | 0.5887 | |
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| 0.4299 | 7.0 | 1855 | 2.3852 | 0.5426 | |
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| 0.2854 | 8.0 | 2120 | 2.7498 | 0.5503 | |
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| 0.2854 | 9.0 | 2385 | 3.1832 | 0.5475 | |
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| 0.1251 | 10.0 | 2650 | 3.3652 | 0.5563 | |
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| 0.1251 | 11.0 | 2915 | 3.4598 | 0.5594 | |
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| 0.0711 | 12.0 | 3180 | 3.5185 | 0.5499 | |
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| 0.0711 | 13.0 | 3445 | 3.5487 | 0.5578 | |
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| 0.0328 | 14.0 | 3710 | 3.8292 | 0.5437 | |
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| 0.0328 | 15.0 | 3975 | 3.8419 | 0.5517 | |
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| 0.013 | 16.0 | 4240 | 3.9292 | 0.5496 | |
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| 0.0089 | 17.0 | 4505 | 3.9444 | 0.5684 | |
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| 0.0089 | 18.0 | 4770 | 4.0013 | 0.5659 | |
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| 0.0025 | 19.0 | 5035 | 4.0913 | 0.5675 | |
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| 0.0025 | 20.0 | 5300 | 4.0899 | 0.5653 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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