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dl-bert – AI Model by nastya-fvxop | AlphaNeural AI
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nastya-fvxop
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dl-bert
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transformers
safetensors
bert
token-classification
generated_from_trainer
BAAI/bge-small-en-v1.5
finetune
mit
endpoints_compatible
us
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dl-bert
This model is a fine-tuned version of
BAAI/bge-small-en-v1.5
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1034
Precision: 0.8909
Recall: 0.9160
F1: 0.9033
Accuracy: 0.9783
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0503
1.0
1250
0.0993
0.8925
0.9063
0.8993
0.9776
0.0472
2.0
2500
0.1054
0.8841
0.9113
0.8975
0.9771
0.0089
3.0
3750
0.1034
0.8909
0.9160
0.9033
0.9783
Framework versions
Transformers 4.56.2
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
