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finetune_t5_small_last

This model is a fine-tuned version of cointegrated/rut5-small on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7367

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: 0.0004
  • train_batch_size: 12
  • eval_batch_size: 12
  • seed: 42
  • gradient_accumulation_steps: 12
  • total_train_batch_size: 144
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 8

Training results

Training Loss Epoch Step Validation Loss
2.8842 0.54 150 2.1580
2.692 1.08 300 2.0038
2.6062 1.62 450 1.9259
2.5237 2.16 600 1.8800
2.4775 2.7 750 1.8504
2.4355 3.24 900 1.8220
2.4075 3.78 1050 1.8016
2.3813 4.33 1200 1.7818
2.3555 4.87 1350 1.7742
2.3521 5.41 1500 1.7602
2.3295 5.95 1650 1.7517
2.3185 6.49 1800 1.7444
2.2994 7.03 1950 1.7416
2.3105 7.57 2100 1.7367

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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