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julieou/
my_awesome_wnut_model_cased_lr

Name: my_awesome_wnut_model_cased_lr
Availability: InStock

generated_from_trainer

distilbert/distilbert-base-cased

finetune

apache-2.0

endpoints_compatible

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my_awesome_wnut_model_cased_lr

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

Loss: 0.3761
Precision: 0.4934
Recall: 0.3791
F1: 0.4287
Accuracy: 0.9445

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: 3e-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	0.2693	0.6050	0.2456	0.3494	0.9385
No log	2.0	426	0.2648	0.5086	0.3012	0.3783	0.9427
0.1638	3.0	639	0.2721	0.5131	0.3624	0.4248	0.9445
0.1638	4.0	852	0.3300	0.5601	0.3716	0.4468	0.9465
0.0339	5.0	1065	0.3394	0.5348	0.3772	0.4424	0.9459
0.0339	6.0	1278	0.3515	0.4989	0.4124	0.4515	0.9452
0.0339	7.0	1491	0.3625	0.5112	0.3809	0.4365	0.9461
0.0106	8.0	1704	0.3761	0.4934	0.3791	0.4287	0.9445

Framework versions

Transformers 5.15.0
Pytorch 2.11.0+cpu
Datasets 4.0.0
Tokenizers 0.22.2

julieou/my_awesome_wnut_model_cased_lr

my_awesome_wnut_model_cased_lr

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

julieou/
my_awesome_wnut_model_cased_lr