biotech-sentiment-A2-deberta-large-ce

• Loss: 1.1233
• F1 Macro: 0.1184
• F1 Weighted: 0.0767
• Accuracy: 0.2159
• F1 Neg: 0.0
• F1 Neu: 0.0
• F1 Pos: 0.3551

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 0.1
• num_epochs: 10

Training results

Framework versions

• Transformers 5.3.0
• Pytorch 2.10.0+cu128
• Datasets 4.8.2
• Tokenizers 0.22.2