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BertQuake – AI Model by ColeD0 | AlphaNeural AI
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ColeD0
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BertQuake
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transformers
safetensors
roberta
text-classification
generated_from_trainer
distilbert/distilroberta-base
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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BertQuake
This model is a fine-tuned version of
distilbert/distilroberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0300
Accuracy: 0.9964
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: 8
eval_batch_size: 8
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
0.0261
1.0
8745
0.0257
0.9955
0.0167
2.0
17490
0.0212
0.9968
0.0042
3.0
26235
0.0266
0.9968
0.0002
4.0
34980
0.0275
0.9963
0.0001
5.0
43725
0.0300
0.9964
Framework versions
Transformers 4.42.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
