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--- |
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base_model: MiMe-MeMo/MeMo-BERT-02 |
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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_2 |
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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_2 |
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This model is a fine-tuned version of [MiMe-MeMo/MeMo-BERT-02](https://huggingface.co/MiMe-MeMo/MeMo-BERT-02) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4358 |
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- F1-score: 0.5924 |
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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 | 1.0171 | 0.5029 | |
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| 0.9806 | 2.0 | 530 | 0.9884 | 0.5416 | |
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| 0.9806 | 3.0 | 795 | 1.1255 | 0.5477 | |
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| 0.6405 | 4.0 | 1060 | 1.0771 | 0.5716 | |
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| 0.6405 | 5.0 | 1325 | 1.4358 | 0.5924 | |
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| 0.3872 | 6.0 | 1590 | 2.0203 | 0.5780 | |
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| 0.3872 | 7.0 | 1855 | 2.4784 | 0.5730 | |
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| 0.2014 | 8.0 | 2120 | 2.7627 | 0.5735 | |
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| 0.2014 | 9.0 | 2385 | 3.1488 | 0.5733 | |
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| 0.0888 | 10.0 | 2650 | 3.2253 | 0.5636 | |
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| 0.0888 | 11.0 | 2915 | 3.4722 | 0.5488 | |
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| 0.0563 | 12.0 | 3180 | 3.6568 | 0.5718 | |
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| 0.0563 | 13.0 | 3445 | 3.8553 | 0.5676 | |
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| 0.0188 | 14.0 | 3710 | 3.8721 | 0.5572 | |
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| 0.0188 | 15.0 | 3975 | 3.9256 | 0.5782 | |
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| 0.0021 | 16.0 | 4240 | 3.9991 | 0.5802 | |
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| 0.0032 | 17.0 | 4505 | 4.0370 | 0.5798 | |
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| 0.0032 | 18.0 | 4770 | 4.1400 | 0.5746 | |
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| 0.0012 | 19.0 | 5035 | 4.1422 | 0.5740 | |
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| 0.0012 | 20.0 | 5300 | 4.1453 | 0.5742 | |
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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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