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finetuning-sentiment-model – AI Model by ruitj | AlphaNeural AI
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finetuning-sentiment-model
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
ProsusAI/finbert
finetune
autotrain_compatible
endpoints_compatible
us
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finetuning-sentiment-model
This model is a fine-tuned version of
ProsusAI/finbert
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.7034
Accuracy: 0.8518
F1: 0.8524
Precision: 0.8532
Recall: 0.8518
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: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
Training results
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1
