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HW4_model_simple – AI Model by eliyashev | AlphaNeural AI
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HW4_model_simple
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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HW4_model_simple
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: 0.0300
Accuracy: 0.9916
F1: 0.6328
Precision: 0.7995
Recall: 0.5236
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.0311
1.0
2050
0.0300
0.9916
0.6328
0.7995
0.5236
Framework versions
Transformers 4.51.0
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
