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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-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: eternis_router_encoder_sft_11Sep |
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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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# eternis_router_encoder_sft_11Sep |
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4944 |
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- Model Accuracy: 0.7861 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- optimizer: Use adamw_torch_fused 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: 0.01 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Model Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------------:| |
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| 0.535 | 1.0602 | 300 | 0.5205 | 0.7730 | |
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| 0.5295 | 2.1204 | 600 | 0.5053 | 0.7764 | |
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| 0.5166 | 3.1805 | 900 | 0.5038 | 0.7811 | |
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| 0.5138 | 4.2407 | 1200 | 0.5009 | 0.7807 | |
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| 0.5196 | 5.3009 | 1500 | 0.5048 | 0.7761 | |
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| 0.4977 | 6.3611 | 1800 | 0.5034 | 0.7795 | |
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| 0.4924 | 7.4212 | 2100 | 0.4970 | 0.7803 | |
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| 0.4915 | 8.4814 | 2400 | 0.5084 | 0.7749 | |
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| 0.4903 | 9.5416 | 2700 | 0.4960 | 0.7830 | |
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| 0.4942 | 10.6018 | 3000 | 0.4945 | 0.7873 | |
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| 0.4926 | 11.6619 | 3300 | 0.4955 | 0.7807 | |
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| 0.5057 | 12.7221 | 3600 | 0.4929 | 0.7826 | |
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| 0.4916 | 13.7823 | 3900 | 0.4939 | 0.7838 | |
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| 0.4953 | 14.8425 | 4200 | 0.4948 | 0.7807 | |
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| 0.4919 | 15.9027 | 4500 | 0.4947 | 0.7834 | |
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| 0.5043 | 16.9628 | 4800 | 0.4944 | 0.7854 | |
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| 0.4768 | 18.0212 | 5100 | 0.4944 | 0.7857 | |
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| 0.4879 | 19.0814 | 5400 | 0.4944 | 0.7861 | |
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### Framework versions |
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- Transformers 4.56.1 |
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- Pytorch 2.8.0+cu128 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.0 |
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