bert-base-uncased-sst2

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

• Loss: 0.2139
• Accuracy: 0.9282

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: 9e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• distributed_type: IPU
• gradient_accumulation_steps: 32
• total_train_batch_size: 2048
• total_eval_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 2
• training precision: Mixed Precision

Training results

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.1+cpu
• Datasets 2.11.0
• Tokenizers 0.12.1