Liu-Xiang
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bert-base-banking77-pt2

Text Classification

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text-embeddings-inference

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bert-base-banking77-pt2

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

Loss: 0.8321
F1: 0.8725

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: 5e-05
train_batch_size: 64
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	157	2.0624	0.6571
2.9518	2.0	314	1.0593	0.8374
1.1419	3.0	471	0.8321	0.8725

Framework versions

Transformers 4.36.0
Pytorch 2.0.1+cu118
Datasets 2.20.0
Tokenizers 0.15.2

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Safetensors

Model size

0.1B params

Tensor type

F32

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Model tree for Liu-Xiang/bert-base-banking77-pt2

Base model

google-bert/bert-base-uncased

Finetuned

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