tiny-bert-sst2-distilled

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tiny-bert-sst2-distilled

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

• eval_loss: 0.3552
• eval_accuracy: 0.8509
• eval_AUC: 0.8049
• eval_MCC: 0.5681
• eval_PR_AUC: 0.6897
• eval_BAC: 0.7295
• eval_runtime: 29.1893
• eval_samples_per_second: 311.176
• eval_steps_per_second: 9.73
• epoch: 1.0
• step: 1224

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: 1.0579519958564978e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 9
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6

Framework versions

• Transformers 4.43.3
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1