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results – AI Model by ranjana1811 | AlphaNeural AI
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peft
safetensors
adapter
lora
transformers
distilbert/distilbert-base-uncased
adapter
apache-2.0
us
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results
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3093
Accuracy: 0.892
F1: 0.8939
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: 0.0002
train_batch_size: 8
eval_batch_size: 8
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
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.3669
1.0
1000
0.3286
0.8825
0.8863
0.4357
2.0
2000
0.3093
0.892
0.8939
Framework versions
PEFT 0.17.1
Transformers 4.57.0
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
