distilbert-base-token – AI Model by PabloGuinea | AlphaNeural AI

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PabloGuinea/
distilbert-base-token

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert-base-token

This model is a fine-tuned version of distilbert-base-uncased on the wnut_17 dataset. It achieves the following results on the evaluation set:

Loss: 0.2714
Precision: 0.5349
Recall: 0.3411
F1: 0.4165
Accuracy: 0.9446

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	107	0.3073	0.3474	0.1223	0.1809	0.9325
No log	2.0	214	0.2605	0.4597	0.2956	0.3598	0.9409
No log	3.0	321	0.2563	0.5319	0.3318	0.4087	0.9431
No log	4.0	428	0.2581	0.5255	0.3531	0.4224	0.9449
0.1669	5.0	535	0.2714	0.5349	0.3411	0.4165	0.9446

Framework versions

Transformers 4.29.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3