finetuned_llm_for_sentiment_analysis

This model is a fine-tuned version of ahmedrachid/FinancialBERT-Sentiment-Analysis on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2301
• Accuracy: 0.9125

Model description

Sentiments:

• 0: "SADNESS"
• 1: "JOY"
• 2: "LOVE"
• 3: "ANGER"
• 4: "FEAR"
• 5: "SURPRISE"

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 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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3986	1.0	1000	0.2892	0.9025
0.1802	2.0	2000	0.2301	0.9125

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0