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jackmedda/google-long-t5-tglobal-base_finetuned_augmented_augmented_smollm2_1.7b

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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jackmedda/google-long-t5-tglobal-basefinetunedaugmentedaugmentedsmollm2_1.7b

This model is a fine-tuned version of google/long-t5-tglobal-base on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.5509
  • —Accuracy: 0.7647
  • —F1: 0.8667
  • —Precision: 0.7647
  • —Recall: 1.0

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: 2
  • —evalbatchsize: 2
  • —seed: 42
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 50

Training results

Training LossEpochStepValidation LossAccuracyF1PrecisionRecall
0.54481.0920.61800.70.82350.71.0
0.22972.01840.82740.70.82350.71.0
0.92013.02761.25380.70.82350.71.0
1.28344.03681.45040.70.82350.71.0
0.68165.04601.50830.70.82350.71.0
0.6796.05521.58010.70.82350.71.0
0.73557.06441.58330.70.82350.71.0
0.46868.07361.53270.70.82350.71.0
0.49049.08281.48040.70.82350.71.0

Framework versions

  • —Transformers 4.48.3
  • —Pytorch 2.3.0+cu121
  • —Datasets 3.2.0
  • —Tokenizers 0.21.0