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results – AI Model by duafatima1207 | AlphaNeural AI
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safetensors
distilbert
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
us
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Model card
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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: 0.4655
Accuracy: 0.862
Precision: 0.8172
Recall: 0.9268
F1: 0.8686
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: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.4334
1.0
125
0.4834
0.804
0.727
0.9634
0.8287
0.2171
2.0
250
0.4086
0.856
0.7979
0.9472
0.8662
0.0965
3.0
375
0.4655
0.862
0.8172
0.9268
0.8686
Framework versions
Transformers 4.41.0
Pytorch 2.11.0+cu128
Datasets 2.20.0
Tokenizers 0.19.1
