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chemical-ner-bert-large-uncased – AI Model by shubhamgantayat | AlphaNeural AI
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shubhamgantayat
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chemical-ner-bert-large-uncased
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-large-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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chemical_ner_bert_large_uncased
This model is a fine-tuned version of
google-bert/bert-large-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1319
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.1709
1.0
716
0.1271
0.1287
2.0
1432
0.1400
0.0917
3.0
2148
0.1319
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
