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results – AI Model by Raj-sharma01 | AlphaNeural AI
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Raj-sharma01
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transformers
tensorboard
safetensors
distilbert
token-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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results
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: 0.0317
Precision: 0.9397
Recall: 0.9605
F1: 0.9500
Accuracy: 0.9902
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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0479
1.0
2180
0.0402
0.9186
0.9507
0.9343
0.9873
0.0265
2.0
4360
0.0336
0.9305
0.9547
0.9424
0.9894
0.016
3.0
6540
0.0317
0.9397
0.9605
0.9500
0.9902
Framework versions
Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
