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my_Ws_extraction_model_26th_mar – AI Model by manimaranpa07 | AlphaNeural AI
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my_Ws_extraction_model_26th_mar
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transformers
safetensors
distilbert
token-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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my_Ws_extraction_model_26th_mar
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: 0.2625
Precision: 0.4942
Recall: 0.4780
F1: 0.4860
Accuracy: 0.9079
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
76
0.2922
0.4641
0.4216
0.4418
0.9028
No log
2.0
152
0.2625
0.4942
0.4780
0.4860
0.9079
Framework versions
Transformers 4.37.2
Pytorch 2.2.0+cu118
Datasets 2.17.0
Tokenizers 0.15.2
