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Pi-Marie/
TinyBERT-distillation-clinc

Name: TinyBERT-distillation-clinc
Availability: InStock

generated_from_trainer

huawei-noah/TinyBERT_General_4L_312D

finetune

text-embeddings-inference

endpoints_compatible

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TinyBERT-distillation-clinc

This model is a fine-tuned version of huawei-noah/TinyBERT_General_4L_312D on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 4.1571
Accuracy: 0.1926

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: 48
eval_batch_size: 48
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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	318	4.7679	0.1123
4.839	2.0	636	4.4874	0.1084
4.839	3.0	954	4.3043	0.1358
4.426	4.0	1272	4.1943	0.1765
4.2081	5.0	1590	4.1571	0.1926

Framework versions

Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0

Pi-Marie/TinyBERT-distillation-clinc

TinyBERT-distillation-clinc

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Pi-Marie/
TinyBERT-distillation-clinc