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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-01 |
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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-01 |
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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: 3.8264 |
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- F1-score: 0.4148 |
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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 | 61 | 1.5574 | 0.1229 | |
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| No log | 2.0 | 122 | 1.4491 | 0.1477 | |
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| No log | 3.0 | 183 | 1.3661 | 0.2112 | |
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| No log | 4.0 | 244 | 1.7131 | 0.3356 | |
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| No log | 5.0 | 305 | 2.0026 | 0.3592 | |
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| No log | 6.0 | 366 | 2.8807 | 0.2263 | |
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| No log | 7.0 | 427 | 2.8357 | 0.3625 | |
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| No log | 8.0 | 488 | 3.5272 | 0.3150 | |
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| 0.7496 | 9.0 | 549 | 3.5185 | 0.3402 | |
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| 0.7496 | 10.0 | 610 | 3.8264 | 0.4148 | |
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| 0.7496 | 11.0 | 671 | 4.5875 | 0.2999 | |
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| 0.7496 | 12.0 | 732 | 4.3188 | 0.3392 | |
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| 0.7496 | 13.0 | 793 | 4.7118 | 0.3098 | |
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| 0.7496 | 14.0 | 854 | 4.5895 | 0.3319 | |
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| 0.7496 | 15.0 | 915 | 4.6764 | 0.3033 | |
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| 0.7496 | 16.0 | 976 | 4.6250 | 0.3319 | |
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| 0.01 | 17.0 | 1037 | 4.7393 | 0.3176 | |
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| 0.01 | 18.0 | 1098 | 4.7690 | 0.3176 | |
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| 0.01 | 19.0 | 1159 | 4.7655 | 0.3176 | |
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| 0.01 | 20.0 | 1220 | 4.7695 | 0.3176 | |
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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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