t5_small_race_mutlirc

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5760
• Accuracy: 0.5259

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: 0.0001
• train_batch_size: 8
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1000
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.6043	1.0	14141	0.4832	0.5925
0.5647	2.0	28282	0.5152	0.5659
0.5237	3.0	42423	0.5760	0.5259

Framework versions

• Transformers 4.11.3
• Pytorch 1.9.1
• Datasets 1.12.1
• Tokenizers 0.10.3