finbert-japan-lora-v1 – AI Model by dgawghbuidw | AlphaNeural AI

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finbert-japan-lora-v1

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ProsusAI/finbert

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finbert-japan-lora-v1

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

Loss: 0.2192
Accuracy: 0.822
F1: 0.8250

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: 0.0002
train_batch_size: 32
eval_batch_size: 32
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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.1955	1.0	733	0.2869	0.744	0.7502
0.0921	2.0	1466	0.2509	0.772	0.7686
0.0606	3.0	2199	0.2283	0.788	0.7868
0.0582	4.0	2932	0.2412	0.812	0.8134
0.0445	5.0	3665	0.2360	0.806	0.8067

Framework versions

PEFT 0.18.0
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.2