distilbert-base-uncased-ner-mit-restaurant – AI Model by andi611 | AlphaNeural AI

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andi611/
distilbert-base-uncased-ner-mit-restaurant

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-ner-mit-restaurant

This model is a fine-tuned version of distilbert-base-uncased on the mit_restaurant dataset. It achieves the following results on the evaluation set:

Loss: 0.3097
Precision: 0.7874
Recall: 0.8104
F1: 0.7988
Accuracy: 0.9119

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: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	431	0.4575	0.6220	0.6856	0.6523	0.8650
1.1705	2.0	862	0.3183	0.7747	0.7953	0.7848	0.9071
0.3254	3.0	1293	0.3163	0.7668	0.8021	0.7841	0.9058
0.2287	4.0	1724	0.3097	0.7874	0.8104	0.7988	0.9119

Framework versions

Transformers 4.8.2
Pytorch 1.8.1+cu111
Datasets 1.8.0
Tokenizers 0.10.3