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--- |
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license: mit |
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base_model: vinai/phobert-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: DACN2 |
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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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# DACN2 |
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This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.1474 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| No log | 1.0 | 347 | 1.1891 | |
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| 1.3935 | 2.0 | 694 | 1.1047 | |
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| 0.8907 | 3.0 | 1041 | 1.0154 | |
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| 0.8907 | 4.0 | 1388 | 1.0854 | |
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| 0.593 | 5.0 | 1735 | 1.3185 | |
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| 0.3795 | 6.0 | 2082 | 1.5470 | |
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| 0.3795 | 7.0 | 2429 | 1.4931 | |
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| 0.2399 | 8.0 | 2776 | 1.6889 | |
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| 0.1596 | 9.0 | 3123 | 1.8808 | |
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| 0.1596 | 10.0 | 3470 | 2.0850 | |
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| 0.1084 | 11.0 | 3817 | 2.3343 | |
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| 0.0806 | 12.0 | 4164 | 2.5696 | |
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| 0.0472 | 13.0 | 4511 | 2.6458 | |
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| 0.0472 | 14.0 | 4858 | 2.7680 | |
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| 0.0485 | 15.0 | 5205 | 2.8165 | |
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| 0.0417 | 16.0 | 5552 | 2.8918 | |
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| 0.0417 | 17.0 | 5899 | 3.0412 | |
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| 0.0233 | 18.0 | 6246 | 3.0186 | |
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| 0.0193 | 19.0 | 6593 | 3.0639 | |
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| 0.0193 | 20.0 | 6940 | 3.0657 | |
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| 0.0191 | 21.0 | 7287 | 2.9095 | |
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| 0.0146 | 22.0 | 7634 | 3.0045 | |
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| 0.0146 | 23.0 | 7981 | 3.2984 | |
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| 0.013 | 24.0 | 8328 | 3.3791 | |
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| 0.0131 | 25.0 | 8675 | 3.2946 | |
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| 0.0101 | 26.0 | 9022 | 3.2814 | |
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| 0.0101 | 27.0 | 9369 | 3.3177 | |
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| 0.0114 | 28.0 | 9716 | 3.2819 | |
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| 0.0046 | 29.0 | 10063 | 3.2945 | |
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| 0.0046 | 30.0 | 10410 | 3.3072 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
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