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Upload fine-tuned RoBERTa model

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: roberta-base
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: emotion_classifier_roberta_optimized
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+ results: []
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+ ---
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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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+
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+ # emotion_classifier_roberta_optimized
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2027
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+ - Macro F1: 0.4232
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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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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+ - 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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 7
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Macro F1 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.2029 | 1.0 | 5227 | 0.1979 | 0.3165 |
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+ | 0.1909 | 2.0 | 10454 | 0.1931 | 0.3674 |
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+ | 0.1808 | 3.0 | 15681 | 0.1923 | 0.4173 |
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+ | 0.1754 | 4.0 | 20908 | 0.1941 | 0.4166 |
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+ | 0.1653 | 5.0 | 26135 | 0.1965 | 0.4275 |
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+ | 0.1576 | 6.0 | 31362 | 0.2009 | 0.4295 |
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+ | 0.1516 | 7.0 | 36589 | 0.2027 | 0.4232 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.51.3
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.6.0
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+ - Tokenizers 0.21.1
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+ "layer_norm_eps": 1e-05,
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