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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: 1.6537 |
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- F1-score: 0.5806 |
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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 | 297 | 0.9994 | 0.4947 | |
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| 0.9854 | 2.0 | 594 | 1.0281 | 0.5454 | |
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| 0.9854 | 3.0 | 891 | 1.1639 | 0.5563 | |
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| 0.6507 | 4.0 | 1188 | 1.6537 | 0.5806 | |
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| 0.6507 | 5.0 | 1485 | 1.7769 | 0.5688 | |
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| 0.404 | 6.0 | 1782 | 2.2283 | 0.5678 | |
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| 0.1759 | 7.0 | 2079 | 2.7271 | 0.5659 | |
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| 0.1759 | 8.0 | 2376 | 3.2521 | 0.5701 | |
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| 0.0906 | 9.0 | 2673 | 3.2777 | 0.5655 | |
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| 0.0906 | 10.0 | 2970 | 3.3451 | 0.5696 | |
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| 0.0717 | 11.0 | 3267 | 3.7121 | 0.5610 | |
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| 0.0299 | 12.0 | 3564 | 3.8619 | 0.5420 | |
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| 0.0299 | 13.0 | 3861 | 3.9670 | 0.5654 | |
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| 0.02 | 14.0 | 4158 | 4.2349 | 0.5409 | |
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| 0.02 | 15.0 | 4455 | 4.2491 | 0.5549 | |
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| 0.0074 | 16.0 | 4752 | 4.4144 | 0.5467 | |
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| 0.006 | 17.0 | 5049 | 4.3564 | 0.5663 | |
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| 0.006 | 18.0 | 5346 | 4.5443 | 0.5616 | |
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| 0.004 | 19.0 | 5643 | 4.5436 | 0.5424 | |
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| 0.004 | 20.0 | 5940 | 4.5248 | 0.5582 | |
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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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