VincentYH
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LLM_B_HW1

Text Classification

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text-embeddings-inference

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LLM_B_HW1

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

Loss: 0.9960
Matthews Correlation: 0.5199

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: 3.529688833764059e-05
train_batch_size: 16
eval_batch_size: 16
seed: 3
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Matthews Correlation
0.5179	1.0	535	0.4566	0.5002
0.3239	2.0	1070	0.5242	0.5154
0.207	3.0	1605	0.7723	0.5131
0.1429	4.0	2140	0.9358	0.5227
0.0818	5.0	2675	0.9960	0.5199

Framework versions

Transformers 4.39.1
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

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Safetensors

Model size

67M params

Tensor type

F32

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