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hello-yes-recall – AI Model by Andesha | AlphaNeural AI
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Andesha
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hello-yes-recall
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transformers
tensorboard
safetensors
modernbert
text-classification
generated_from_trainer
answerdotai/ModernBERT-base
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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hello-yes-recall
This model is a fine-tuned version of
answerdotai/ModernBERT-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.8338
F1: 0.6895
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: 5e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
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
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
F1
0.9868
1.0
238
0.9431
0.5981
0.8795
2.0
476
0.8704
0.6700
0.7862
3.0
714
0.8379
0.6825
0.7416
4.0
952
0.8342
0.6878
0.7368
5.0
1190
0.8338
0.6895
Framework versions
Transformers 4.57.1
Pytorch 2.7.1
Datasets 4.3.0
Tokenizers 0.22.1
