train-bioR-concat-gen1

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

• Loss: 1.3226

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: 0.001
• train_batch_size: 48
• eval_batch_size: 48
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• total_train_batch_size: 192
• total_eval_batch_size: 192
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 1000
• training_steps: 23848
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.5839	0.4193	10000	1.3249
0.5677	0.8386	20000	1.3226

Framework versions

• Transformers 4.53.0
• Pytorch 2.5.1
• Datasets 3.6.0
• Tokenizers 0.21.2