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emotion_classifier_roberta_optimized

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
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Upload fine-tuned RoBERTa model

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  1. README.md +11 -11
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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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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  ## Model description
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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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  | 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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  ### Framework versions
 
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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: 0.1972
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+ - Macro F1: 0.4889
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  ## Model description
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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: 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=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Macro F1 |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.2093 | 1.0 | 2614 | 0.2019 | 0.4586 |
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+ | 0.1941 | 2.0 | 5228 | 0.1938 | 0.4815 |
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+ | 0.1845 | 3.0 | 7842 | 0.1916 | 0.4921 |
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+ | 0.1764 | 4.0 | 10456 | 0.1928 | 0.4918 |
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+ | 0.1699 | 5.0 | 13070 | 0.1936 | 0.4963 |
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+ | 0.1639 | 6.0 | 15684 | 0.1964 | 0.4872 |
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+ | 0.1608 | 7.0 | 18298 | 0.1972 | 0.4889 |
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  ### Framework versions
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