modernbert_large_likes_predictor

This model is a fine-tuned version of answerdotai/ModernBERT-large on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2319
• Rmse: 0.2319
• Mae: 0.3442

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: 6.000000000000001e-05
• train_batch_size: 2
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 12
• total_train_batch_size: 24
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.15
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Rmse	Mae
3.0522	0.4971	150	0.3021	0.3021	0.4136
3.7437	0.9942	300	0.3355	0.3355	0.4575
3.0905	1.4905	450	0.2626	0.2626	0.3680
1.7883	1.9876	600	0.2319	0.2319	0.3442

Framework versions

• Transformers 4.52.4
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1