quicky-ai

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.3098
• Accuracy: 0.8727

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 32
• seed: 42
• distributed_type: tpu
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3063	1.0	4210	0.3110	0.8704
0.2875	2.0	8420	0.3098	0.8727

Framework versions

• Transformers 5.0.0
• Pytorch 2.9.0+cpu
• Datasets 4.8.4
• Tokenizers 0.22.2