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julieou/
my_awesome_wnut_model_lrx2

Name: my_awesome_wnut_model_lrx2
Availability: InStock

generated_from_trainer

distilbert/distilbert-base-uncased

finetune

apache-2.0

endpoints_compatible

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my_awesome_wnut_model_lrx2

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

Loss: 0.3524
Precision: 0.6255
Recall: 0.3049
F1: 0.4100
Accuracy: 0.9449

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: 4e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	213	0.2599	0.6709	0.3401	0.4514	0.9431
No log	2.0	426	0.2835	0.6239	0.3197	0.4228	0.9452
0.1381	3.0	639	0.3524	0.6255	0.3049	0.4100	0.9449

Framework versions

Transformers 5.15.0
Pytorch 2.11.0+cpu
Datasets 4.0.0
Tokenizers 0.22.2

julieou/my_awesome_wnut_model_lrx2

my_awesome_wnut_model_lrx2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

julieou/
my_awesome_wnut_model_lrx2