matscibert-finetuned

This model is a fine-tuned version of m3rg-iitd/matscibert on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0261
• Accuracy: 0.9941

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: 16
• seed: 42
• optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.037	0.8446	500	0.0362	0.9924
0.0216	1.6892	1000	0.0273	0.9934
0.0103	2.5338	1500	0.0261	0.9941

Framework versions

• Transformers 4.56.1
• Pytorch 2.8.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.0