lora_sentiment_analysis

This model is a fine-tuned version of ministral/Ministral-3b-instruct on the generator dataset. It achieves the following results on the evaluation set:

• Loss: 0.7821

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: 0.0005
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 8
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
9.3704	1.0	262	1.1464
7.0922	2.0	524	0.8622
5.1725	2.9890	783	0.7821

Framework versions

• PEFT 0.14.0
• Transformers 4.48.0
• Pytorch 2.1.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0