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gonzalezrostani/
my_awesome_wnut_all_JAOa

Name: my_awesome_wnut_all_JAOa
Availability: InStock

generated_from_trainer

distilbert/distilbert-base-uncased

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my_awesome_wnut_all_JAOa

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: 0.0970
Precision: 0.4829
Recall: 0.4652
F1: 0.4739
Accuracy: 0.9748

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	0.0810	0.4868	0.3370	0.3983	0.9748
0.0831	2.0	502	0.0850	0.5333	0.3810	0.4444	0.9759
0.0831	3.0	753	0.0894	0.4906	0.4762	0.4833	0.9750
0.0431	4.0	1004	0.0970	0.4829	0.4652	0.4739	0.9748

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cpu
Datasets 2.18.0
Tokenizers 0.15.2

gonzalezrostani/my_awesome_wnut_all_JAOa

my_awesome_wnut_all_JAOa

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gonzalezrostani/
my_awesome_wnut_all_JAOa