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results – AI Model by IvanShliakhtenko | AlphaNeural AI
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IvanShliakhtenko
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results
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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Model card
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This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6860
Accuracy: 0.8535
F1: 0.8535
Precision: 0.8535
Recall: 0.8535
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: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 22857
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.7794
1.0
38097
0.7224
0.8412
0.8411
0.8422
0.8412
0.6540
2.0
76194
0.6935
0.8506
0.8506
0.8506
0.8506
0.5121
3.0
114291
0.7561
0.8504
0.8504
0.8506
0.8504
Framework versions
Transformers 5.15.1
Pytorch 2.10.0+cu128
Datasets 5.0.1
Tokenizers 0.22.2
