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akseljoonas/f2llm-sentiment-ablation-A

sourceHugging Faceapache-2.0updated 7mo agoView on Hugging Face
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f2llm-sentiment-ablation-A

This model is a fine-tuned version of codefuse-ai/F2LLM-0.6B on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.3227
  • F1 Macro: 0.4165
  • F1 Weighted: 0.5401
  • Accuracy: 0.5592

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: 2e-05
  • trainbatchsize: 16
  • evalbatchsize: 32
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lrschedulertype: linear
  • lrschedulerwarmup_steps: 0.1
  • num_epochs: 10

Training results

Training LossEpochStepValidation LossF1 MacroF1 WeightedAccuracy
0.93171.02220.99210.30710.48990.5921
0.89622.04440.93610.34590.51650.6118
0.77363.06660.96220.38770.53120.5829
0.49204.08881.27100.42710.54840.5724
0.18945.011101.83210.41980.51070.4974
0.10136.013322.02210.43630.54510.5513
0.09477.015542.18990.42090.54370.5632
0.02078.017762.30200.42700.54510.5605
0.04009.019982.31260.42220.54360.5605
0.010210.022202.32270.41650.54010.5592

Framework versions

  • Transformers 5.3.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.7.0
  • Tokenizers 0.22.2