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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-WSD-MeMo-BERT-02_last |
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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-WSD-MeMo-BERT-02_last |
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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: 3.3216 |
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- F1-score: 0.4444 |
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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 | 1.6200 | 0.1229 | |
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| No log | 2.0 | 122 | 1.4272 | 0.2217 | |
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| No log | 3.0 | 183 | 1.4465 | 0.2220 | |
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| No log | 4.0 | 244 | 1.7271 | 0.2428 | |
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| No log | 5.0 | 305 | 1.8954 | 0.3110 | |
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| No log | 6.0 | 366 | 2.7308 | 0.1632 | |
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| No log | 7.0 | 427 | 2.3096 | 0.3502 | |
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| No log | 8.0 | 488 | 2.5584 | 0.4155 | |
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| 0.8087 | 9.0 | 549 | 3.1863 | 0.4054 | |
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| 0.8087 | 10.0 | 610 | 3.3216 | 0.4444 | |
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| 0.8087 | 11.0 | 671 | 3.3437 | 0.3938 | |
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| 0.8087 | 12.0 | 732 | 4.1038 | 0.3355 | |
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| 0.8087 | 13.0 | 793 | 4.4369 | 0.3054 | |
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| 0.8087 | 14.0 | 854 | 3.8867 | 0.3430 | |
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| 0.8087 | 15.0 | 915 | 3.9579 | 0.3430 | |
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| 0.8087 | 16.0 | 976 | 4.0195 | 0.3430 | |
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| 0.0152 | 17.0 | 1037 | 4.1380 | 0.3311 | |
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| 0.0152 | 18.0 | 1098 | 4.1298 | 0.3311 | |
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| 0.0152 | 19.0 | 1159 | 4.1499 | 0.3311 | |
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| 0.0152 | 20.0 | 1220 | 4.1574 | 0.3311 | |
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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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