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ppak10/
defect-classification-scibert-baseline-10-epochs

transformers

safetensors

generated_from_trainer

allenai/scibert_scivocab_uncased

finetune

endpoints_compatible

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defect-classification-scibert-baseline-10-epochs

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

Loss: 0.2965
Accuracy: 0.8886

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: 256
eval_batch_size: 256
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3829	1.0	2124	0.6337	0.8424
1.0008	2.0	4248	0.4279	0.8789
0.8108	3.0	6372	0.3942	0.8808
0.7122	4.0	8496	0.3775	0.8769
0.6473	5.0	10620	0.3395	0.8816
0.622	6.0	12744	0.3346	0.8806
0.5915	7.0	14868	0.3135	0.8842
0.5661	8.0	16992	0.3008	0.8887
0.559	9.0	19116	0.2914	0.8910
0.5623	10.0	21240	0.2965	0.8886

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0

ppak10/defect-classification-scibert-baseline-10-epochs

defect-classification-scibert-baseline-10-epochs

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ppak10/
defect-classification-scibert-baseline-10-epochs