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adith-ds/emotion-classifier-v2
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metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
model-index:
  - name: results
    results: []

results

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3095
  • Macro F1: 0.8317
  • Macro Precision: 0.8609
  • Macro Recall: 0.8061
  • Macro Support: None

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • 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: 500
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Macro F1 Macro Precision Macro Recall Macro Support
No log 1.0 86 0.5550 0.1427 0.1109 0.2 None
0.6112 2.0 172 0.4244 0.5106 0.7966 0.4864 None
0.4482 3.0 258 0.3317 0.7370 0.7756 0.7129 None
0.3083 4.0 344 0.3029 0.7749 0.8252 0.7414 None
0.2015 5.0 430 0.2997 0.7893 0.8241 0.7742 None
0.1252 6.0 516 0.2980 0.8110 0.8430 0.7882 None
0.0736 7.0 602 0.3023 0.8148 0.8565 0.7811 None
0.0736 8.0 688 0.3091 0.8279 0.8448 0.8135 None
0.0384 9.0 774 0.3087 0.8313 0.8613 0.8062 None
0.0216 10.0 860 0.3095 0.8317 0.8609 0.8061 None

Framework versions

  • Transformers 4.57.1
  • Pytorch 2.8.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.22.1