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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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model-index:
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- name: EMOTION-AI-modernbert-large
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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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# EMOTION-AI-modernbert-large
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This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co./answerdotai/ModernBERT-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.7181
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- Accuracy: 0.5725
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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: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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: linear
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- num_epochs: 4
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:--------:|
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| 6.7571 | 1.0 | 645 | 1.3419 | 0.5689 |
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| 4.9223 | 2.0 | 1290 | 1.2715 | 0.5910 |
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| 3.9903 | 3.0 | 1935 | 1.4913 | 0.5767 |
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| 1.32 | 3.9946 | 2576 | 1.7181 | 0.5725 |
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### Framework versions
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- Transformers 4.48.0.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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