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finbert_lora – AI Model by Hemanth7774 | AlphaNeural AI
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Hemanth7774
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finbert_lora
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peft
safetensors
adapter
lora
transformers
ProsusAI/finbert
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finbert_lora
This model is a fine-tuned version of
ProsusAI/finbert
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3124
Accuracy: 0.8630
Precision: 0.8480
Recall: 0.8562
F1: 0.8521
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: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.3374
1.0
5013
0.3304
0.8518
0.8172
0.8739
0.8446
0.3287
2.0
10026
0.3101
0.8633
0.8458
0.8603
0.8530
Framework versions
PEFT 0.18.0
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.2
