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bert-sdg-classification – AI Model by albertmartinez | AlphaNeural AI | AlphaNeural AI
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albertmartinez
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bert-sdg-classification
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transformers
onnx
safetensors
bert
text-classification
generated_from_trainer
albertmartinez/OSDG
google-bert/bert-base-uncased
quantized
10.57967/hf/2732
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-sdg-classification
This model is a fine-tuned version of
google-bert/bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.7055
F1: 0.7980
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-05
train_batch_size: 64
eval_batch_size: 64
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
lr_scheduler_warmup_steps: 600
num_epochs: 5.0
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
F1
2.2299
1.0
538
1.0520
0.7118
0.9383
2.0
1076
0.7800
0.7794
0.7379
3.0
1614
0.7253
0.7947
0.6362
4.0
2152
0.7107
0.7965
0.5779
5.0
2690
0.7055
0.7980
Framework versions
Transformers 4.49.0.dev0
Pytorch 2.1.2.post304
Datasets 3.2.0
Tokenizers 0.21.0
