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--- |
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library_name: peft |
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license: apache-2.0 |
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base_model: bert-base-multilingual-cased |
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tags: |
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- base_model:adapter:bert-base-multilingual-cased |
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- lora |
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- transformers |
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model-index: |
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- name: BERT |
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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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# BERT |
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9472 |
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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: 0.0002 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.5892 | 0.0674 | 100 | 1.9698 | |
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| 2.2573 | 0.1347 | 200 | 2.0053 | |
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| 2.1211 | 0.2021 | 300 | 1.9714 | |
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| 2.1551 | 0.2695 | 400 | 1.9574 | |
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| 2.181 | 0.3368 | 500 | 1.9433 | |
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| 2.1707 | 0.4042 | 600 | 1.9536 | |
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| 2.1463 | 0.4715 | 700 | 1.9302 | |
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| 2.1451 | 0.5389 | 800 | 1.9041 | |
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| 2.1099 | 0.6063 | 900 | 1.9010 | |
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| 2.1178 | 0.6736 | 1000 | 1.9308 | |
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| 2.1292 | 0.7410 | 1100 | 1.9336 | |
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| 2.1285 | 0.8084 | 1200 | 1.8931 | |
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| 2.0634 | 0.8757 | 1300 | 1.9067 | |
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| 2.1118 | 0.9431 | 1400 | 1.9244 | |
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| 2.0807 | 1.0101 | 1500 | 1.8401 | |
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| 2.0402 | 1.0775 | 1600 | 1.8851 | |
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| 2.1129 | 1.1448 | 1700 | 1.8613 | |
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| 2.0707 | 1.2122 | 1800 | 1.9472 | |
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### Framework versions |
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- PEFT 0.16.0 |
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- Transformers 4.53.2 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.2 |
