roberta-emotions-8-4-1.1

This model is a fine-tuned version of FacebookAI/roberta-base. It achieves the following results on the evaluation set:

  • Loss: 1.2437
  • F1 Micro: 0.8214
  • F1 Macro: 0.7822
  • Precision Micro: 0.8586
  • Recall Micro: 0.7874

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 48
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1572
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Micro F1 Macro Precision Micro Recall Micro
1.2652 1.0 5240 1.2620 0.8011 0.7596 0.8422 0.7638
1.2534 2.0 10480 1.2509 0.8179 0.7854 0.8501 0.7881
1.2371 3.0 15720 1.2468 0.8251 0.7922 0.8621 0.7912

Framework versions

  • Transformers 5.10.2
  • Pytorch 2.11.0+cu128
  • Datasets 4.8.5
  • Tokenizers 0.22.2
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