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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: answerdotai/ModernBERT-large |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: ModernBERT-large-hinglish-binary |
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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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# ModernBERT-large-hinglish-binary |
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This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6142 |
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- Accuracy: 0.6747 |
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- Precision: 0.6564 |
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- Recall: 0.5824 |
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- F1: 0.5687 |
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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: 32 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 2.622 | 1.0 | 26 | 0.6508 | 0.6349 | 0.5900 | 0.5758 | 0.5758 | |
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| 2.5166 | 2.0 | 52 | 0.6293 | 0.6703 | 0.7476 | 0.5500 | 0.4956 | |
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| 2.5527 | 3.0 | 78 | 0.6549 | 0.6022 | 0.6064 | 0.6150 | 0.5961 | |
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| 2.3672 | 4.0 | 104 | 0.5995 | 0.6975 | 0.7001 | 0.6087 | 0.6017 | |
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| 1.9234 | 5.0 | 130 | 0.6055 | 0.6839 | 0.6574 | 0.6564 | 0.6569 | |
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| 0.9818 | 6.0 | 156 | 0.8319 | 0.6676 | 0.6434 | 0.6468 | 0.6448 | |
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| 0.3056 | 7.0 | 182 | 0.9884 | 0.6730 | 0.6484 | 0.6511 | 0.6495 | |
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| 0.0518 | 8.0 | 208 | 1.2367 | 0.6730 | 0.6492 | 0.6527 | 0.6506 | |
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| 0.0083 | 9.0 | 234 | 1.2961 | 0.6839 | 0.6586 | 0.6596 | 0.6591 | |
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| 0.0023 | 9.6214 | 250 | 1.3402 | 0.6948 | 0.6664 | 0.6471 | 0.6518 | |
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### Framework versions |
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- Transformers 4.48.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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