Model save
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- model.safetensors +1 -1
- tokenizer.json +1 -6
README.md
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---
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metrics:
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- accuracy
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- f1
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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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metrics:
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- f1
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- accuracy
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model-index:
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- name: ModernEMO-base
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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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# ModernEMO-base
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2224
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- F1: 0.7037
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- Roc Auc: 0.8143
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- Accuracy: 0.6226
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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: 8e-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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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| 0.2162 | 1.0 | 2714 | 0.2049 | 0.6920 | 0.7979 | 0.6010 |
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| 0.1553 | 2.0 | 5428 | 0.2224 | 0.7037 | 0.8143 | 0.6226 |
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### Framework versions
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- Transformers 4.49.0.dev0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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model.safetensors
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tokenizer.json
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