finbert_india_finetuned – AI Model by VaibhavLearnsAI | AlphaNeural AI

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VaibhavLearnsAI/
finbert_india_finetuned

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text-classification

generated_from_trainer

Vansh180/FinBERT-India-v1

text-embeddings-inference

endpoints_compatible

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finbert_india_finetuned

This model is a fine-tuned version of Vansh180/FinBERT-India-v1 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2424
Accuracy: 0.9409
F1 Weighted: 0.9405
F1 Macro: 0.9404

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: 16
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
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: cosine
lr_scheduler_warmup_steps: 0.1
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Weighted	F1 Macro
0.2847	1.0	47	0.1477	0.9622	0.9611	0.9569
0.1266	2.0	94	0.2767	0.9459	0.9462	0.9433
0.1077	3.0	141	0.1918	0.9730	0.9727	0.9727
0.0202	4.0	188	0.1949	0.9730	0.9727	0.9727
0.0034	5.0	235	0.1964	0.9730	0.9727	0.9727

Framework versions

Transformers 5.10.1
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2