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fixed_model – AI Model by Raneem5 | AlphaNeural AI | AlphaNeural AI
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fixed_model
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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fixed_model
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: 0.8154
Accuracy: 0.6381
Macro F1: 0.6360
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: 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
Macro F1
0.8349
1.0
748
0.8319
0.5960
0.5943
0.6236
2.0
1496
0.8154
0.6381
0.6360
Framework versions
Transformers 4.57.6
Pytorch 2.11.0+cpu
Datasets 2.21.0
Tokenizers 0.22.2
