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vision_mbert_1024_v1 – AI Model by Dawn123666 | AlphaNeural AI
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vision_mbert_1024_v1
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transformers
safetensors
modernbert
text-classification
generated_from_trainer
answerdotai/ModernBERT-base
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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vision_mbert_1024_v1
This model is a fine-tuned version of
answerdotai/ModernBERT-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1928
F1: 0.8122
Precision: 0.7328
Recall: 0.9107
Accuracy: 0.9157
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
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 4
total_train_batch_size: 128
total_eval_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: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
F1
Precision
Recall
Accuracy
1.1597
1.0
351
0.2048
0.7908
0.6853
0.9348
0.9011
0.8152
2.0
702
0.1951
0.8112
0.7307
0.9117
0.9151
0.6848
3.0
1053
0.1928
0.8122
0.7328
0.9107
0.9157
Framework versions
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.5.0
Tokenizers 0.22.1
