finetune_t5_small_only_hack

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: 1.8151

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: 18
• eval_batch_size: 18
• seed: 42
• gradient_accumulation_steps: 12
• total_train_batch_size: 216
• 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
2.3143	3.25	150	1.9318
2.0926	6.51	300	1.8151

Framework versions

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