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best-appropriateness-feedback-model – AI Model by timonziegenbein | AlphaNeural AI
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best-appropriateness-feedback-model
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transformers
safetensors
modernbert
token-classification
generated_from_trainer
answerdotai/ModernBERT-large
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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best-appropriateness-feedback-model
This model is a fine-tuned version of
answerdotai/ModernBERT-large
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.7638
Precision: 0.4946
Recall: 0.1040
F1: 0.1719
Accuracy: 0.6764
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: 1.2442675064972576e-05
train_batch_size: 8
eval_batch_size: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
64
0.7551
0.2798
0.0615
0.1008
0.6615
No log
2.0
128
0.7311
0.4009
0.1635
0.2322
0.6718
No log
3.0
192
0.7638
0.4946
0.1040
0.1719
0.6764
Framework versions
Transformers 4.53.0
Pytorch 2.7.1+cu126
Datasets 3.6.0
Tokenizers 0.21.2
