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bert_affinity_pred – AI Model by DaInternet12 | AlphaNeural AI
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bert_affinity_pred
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results
This model is a fine-tuned version of
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6862
Mse: 0.6862
Mae: 0.6459
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: 1e-06
weight_decay: 3e-5
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use lamb_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Mse
Mae
0.4487
1.1416
500
0.7357
0.7357
0.6692
0.7676
2.2831
1000
0.7138
0.7138
0.6618
0.7356
3.4247
1500
0.6736
0.6736
0.6426
0.5261
4.5662
2000
0.6592
0.6592
0.6393
Framework versions
Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
