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--- |
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base_model: MiMe-MeMo/MeMo-BERT-03 |
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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 |
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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_MeMo-BERT-03_01 |
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This model is a fine-tuned version of [MiMe-MeMo/MeMo-BERT-03](https://huggingface.co/MiMe-MeMo/MeMo-BERT-03) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3157 |
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- F1-score: 0.7821 |
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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 | 0.7332 | 0.7373 | |
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| 0.5945 | 2.0 | 594 | 0.9941 | 0.7644 | |
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| 0.5945 | 3.0 | 891 | 1.1745 | 0.7714 | |
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| 0.2243 | 4.0 | 1188 | 1.6828 | 0.7210 | |
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| 0.2243 | 5.0 | 1485 | 1.6114 | 0.7308 | |
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| 0.0807 | 6.0 | 1782 | 1.9495 | 0.7515 | |
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| 0.0133 | 7.0 | 2079 | 2.0289 | 0.7536 | |
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| 0.0133 | 8.0 | 2376 | 2.1528 | 0.7566 | |
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| 0.0002 | 9.0 | 2673 | 2.2011 | 0.7560 | |
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| 0.0002 | 10.0 | 2970 | 2.2830 | 0.7351 | |
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| 0.0199 | 11.0 | 3267 | 2.3461 | 0.7456 | |
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| 0.0103 | 12.0 | 3564 | 2.2212 | 0.7533 | |
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| 0.0103 | 13.0 | 3861 | 2.2322 | 0.7622 | |
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| 0.0063 | 14.0 | 4158 | 2.3226 | 0.7599 | |
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| 0.0063 | 15.0 | 4455 | 2.3019 | 0.7561 | |
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| 0.0026 | 16.0 | 4752 | 2.2407 | 0.7675 | |
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| 0.0 | 17.0 | 5049 | 2.2745 | 0.7715 | |
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| 0.0 | 18.0 | 5346 | 2.3114 | 0.7716 | |
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| 0.0002 | 19.0 | 5643 | 2.3157 | 0.7821 | |
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| 0.0002 | 20.0 | 5940 | 2.3187 | 0.7749 | |
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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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