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llma-finetuned-ner – AI Model by pnr-svc | AlphaNeural AI
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llma-finetuned-ner
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transformers
tensorboard
safetensors
llama
token-classification
generated_from_trainer
afmck/testing-llama-tiny
finetune
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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llma-finetuned-ner
This model is a fine-tuned version of
afmck/testing-llama-tiny
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1003
Precision: 0.9755
Recall: 0.9764
F1: 0.9759
Accuracy: 0.9815
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: 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
0.0726
1.0
5285
0.1305
0.9820
0.9672
0.9745
0.9749
0.0558
2.0
10570
0.1090
0.9733
0.9740
0.9737
0.9796
0.07
3.0
15855
0.1003
0.9755
0.9764
0.9759
0.9815
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1
