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hscore-balanced – AI Model by spidersouris | AlphaNeural AI
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spidersouris
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hscore-balanced
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transformers
tensorboard
safetensors
camembert
text-classification
hyperparameter-search
best-trial
generated_from_trainer
almanach/camembert-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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hscore-balanced
This model is a fine-tuned version of
camembert-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2353
Accuracy: 0.9274
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: 8.497821083760116e-06
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.1801
1.0
1643
0.2273
0.9200
0.3525
2.0
3286
0.2126
0.9266
0.0821
3.0
4929
0.2383
0.9291
0.4058
4.0
6572
0.2149
0.9283
0.2079
5.0
8215
0.2353
0.9274
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1
