tinybert-meld-results

This model is a fine-tuned version of Rudra2002019/tiny-bert-sst2-distilled on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 1.2952
• eval_model_preparation_time: 0.0
• eval_accuracy: 0.5667
• eval_runtime: 48.1414
• eval_samples_per_second: 54.215
• eval_steps_per_second: 6.792
• step: 0

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: 8
• seed: 42
• 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: 20

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cpu
• Datasets 3.5.1
• Tokenizers 0.21.1