Fariman/google_electra-small-discriminator

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google_electra-small-discriminator

This model is a fine-tuned version of google/electra-small-discriminator on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.5391
• —Accuracy: 0.8906
• —F1 Macro: 0.4073
• —Precision Destination: 0.9266
• —Recall Destination: 0.9597
• —Precision Origin: 0.6034
• —Recall Origin: 0.7955
• —Precision Other: 0.0
• —Recall Other: 0.0
• —Precision Transit: 0.0
• —Recall Transit: 0.0
• —Super Metric: 1.7552
• —Raw Super Metric: 1.7552

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: 16
• —seed: 42
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —num_epochs: 10
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.51.3
• —Pytorch 2.6.0+cu124
• —Datasets 3.5.0
• —Tokenizers 0.21.1