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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: memo3_FGN |
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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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# memo3_FGN |
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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: 1.3348 |
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- F1-score: 0.8316 |
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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 | 120 | 0.4934 | 0.8027 | |
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| No log | 2.0 | 240 | 0.5542 | 0.8121 | |
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| No log | 3.0 | 360 | 0.8229 | 0.8168 | |
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| No log | 4.0 | 480 | 0.9300 | 0.8123 | |
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| 0.4028 | 5.0 | 600 | 1.1413 | 0.8057 | |
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| 0.4028 | 6.0 | 720 | 1.3327 | 0.7989 | |
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| 0.4028 | 7.0 | 840 | 1.5178 | 0.7851 | |
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| 0.4028 | 8.0 | 960 | 1.1979 | 0.8299 | |
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| 0.0435 | 9.0 | 1080 | 1.2149 | 0.8307 | |
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| 0.0435 | 10.0 | 1200 | 1.2327 | 0.8302 | |
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| 0.0435 | 11.0 | 1320 | 1.2521 | 0.8312 | |
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| 0.0435 | 12.0 | 1440 | 1.2734 | 0.8304 | |
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| 0.0238 | 13.0 | 1560 | 1.3348 | 0.8316 | |
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| 0.0238 | 14.0 | 1680 | 1.3715 | 0.8181 | |
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| 0.0238 | 15.0 | 1800 | 1.4095 | 0.8064 | |
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| 0.0238 | 16.0 | 1920 | 1.4157 | 0.8179 | |
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| 0.0099 | 17.0 | 2040 | 1.4234 | 0.8179 | |
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| 0.0099 | 18.0 | 2160 | 1.4038 | 0.8127 | |
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| 0.0099 | 19.0 | 2280 | 1.4404 | 0.8117 | |
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| 0.0099 | 20.0 | 2400 | 1.4436 | 0.8117 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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