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End of training
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metadata
base_model: klue/roberta-large
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: pogny-32-0.00001-all
    results: []

pogny-32-0.00001-all

This model is a fine-tuned version of klue/roberta-large on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8361
  • Accuracy: 0.7189
  • F1: 0.7172

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: 1e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.0974 1.0 2554 1.4482 0.7257 0.7216
0.0699 2.0 5108 1.6362 0.7202 0.7178
0.051 3.0 7662 1.8361 0.7189 0.7172

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0a0+b5021ba
  • Datasets 2.6.2
  • Tokenizers 0.14.1