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NER-DL3.5-HW – AI Model by kruglm | AlphaNeural AI
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NER-DL3.5-HW
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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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NER-DL3.5-HW
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: 0.1039
Precision: 0.0143
Recall: 0.9006
F1: 0.0282
Accuracy: 0.2446
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: 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
0.2377
1.0
1250
0.1485
0.0134
0.8388
0.0264
0.2475
0.1208
2.0
2500
0.1101
0.0142
0.8915
0.0280
0.2447
0.0861
3.0
3750
0.1039
0.0143
0.9006
0.0282
0.2446
Framework versions
Transformers 5.2.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
