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finetune_t5_base_only_hack

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

  • Loss: 1.4584

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 256
  • 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
1.8215 3.86 150 1.5392
1.579 7.72 300 1.4584

Framework versions

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