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model3e_no_wd_no_perturb – AI Model by cria111 | AlphaNeural AI
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cria111
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model3e_no_wd_no_perturb
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transformers
tensorboard
safetensors
distilbert
token-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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model3e_no_wd_no_perturb
This model is a fine-tuned version of
distilbert/distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1537
Precision: 0.4272
Recall: 0.4190
F1: 0.4231
Accuracy: 0.9619
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: 2e-05
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
103
0.1871
0.2210
0.0968
0.1347
0.9497
No log
2.0
206
0.1586
0.3525
0.3794
0.3654
0.9575
No log
3.0
309
0.1537
0.4272
0.4190
0.4231
0.9619
Framework versions
Transformers 4.38.2
Pytorch 2.2.0+cpu
Datasets 2.18.0
Tokenizers 0.15.2
