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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: 1.1432 |
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- F1-score: 0.5216 |
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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 | 1.0214 | 0.4174 | |
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| 1.0021 | 2.0 | 594 | 1.0031 | 0.4947 | |
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| 1.0021 | 3.0 | 891 | 1.1432 | 0.5216 | |
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| 0.7732 | 4.0 | 1188 | 1.5043 | 0.4980 | |
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| 0.7732 | 5.0 | 1485 | 2.0586 | 0.4878 | |
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| 0.5308 | 6.0 | 1782 | 1.9069 | 0.4611 | |
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| 0.4125 | 7.0 | 2079 | 2.4514 | 0.4807 | |
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| 0.4125 | 8.0 | 2376 | 2.7144 | 0.4941 | |
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| 0.2539 | 9.0 | 2673 | 2.7355 | 0.5074 | |
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| 0.2539 | 10.0 | 2970 | 3.4404 | 0.5034 | |
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| 0.1538 | 11.0 | 3267 | 3.6571 | 0.4976 | |
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| 0.107 | 12.0 | 3564 | 3.8279 | 0.4992 | |
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| 0.107 | 13.0 | 3861 | 3.8366 | 0.4825 | |
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| 0.0402 | 14.0 | 4158 | 4.1133 | 0.4942 | |
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| 0.0402 | 15.0 | 4455 | 4.2386 | 0.4851 | |
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| 0.0434 | 16.0 | 4752 | 4.4226 | 0.4938 | |
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| 0.0127 | 17.0 | 5049 | 4.5016 | 0.5051 | |
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| 0.0127 | 18.0 | 5346 | 4.5485 | 0.5000 | |
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| 0.0064 | 19.0 | 5643 | 4.6323 | 0.4810 | |
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| 0.0064 | 20.0 | 5940 | 4.6424 | 0.4885 | |
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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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