biotech-sentiment-test-A2-deberta-large-ce

This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 2.6649
• F1 Macro: 0.1197
• F1 Weighted: 0.0785
• Accuracy: 0.2188
• F1 Neg: 0.3590
• F1 Neu: 0.0
• F1 Pos: 0.0

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: 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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Macro	F1 Weighted	Accuracy	F1 Neg	F1 Neu	F1 Pos
No log	1.0	4	1.1427	0.1266	0.0890	0.2344	0.0	0.0	0.3797
No log	2.0	8	2.6649	0.1197	0.0785	0.2188	0.3590	0.0	0.0

Framework versions

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