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gonzalezrostani/
my_awesome_wnut_Them_all

Name: my_awesome_wnut_Them_all
Availability: InStock

generated_from_trainer

distilbert/distilbert-base-uncased

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my_awesome_wnut_Them_all

This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0906
Precision: 0.5194
Recall: 0.5282
F1: 0.5238
Accuracy: 0.9716

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	251	0.0860	0.5923	0.3898	0.4702	0.9681
0.079	2.0	502	0.0782	0.5342	0.5508	0.5424	0.9723
0.079	3.0	753	0.0854	0.5234	0.5367	0.5300	0.9711
0.0347	4.0	1004	0.0906	0.5194	0.5282	0.5238	0.9716

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cpu
Datasets 2.18.0
Tokenizers 0.15.2

gonzalezrostani/my_awesome_wnut_Them_all

my_awesome_wnut_Them_all

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gonzalezrostani/
my_awesome_wnut_Them_all