test2

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.2451
• Accuracy: 0.3922
• F1: 0.3732
• Precision: 0.3777
• Recall: 0.3824

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: 0.0003
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.2543	0.02	16	1.2451	0.3922	0.3732	0.3777	0.3824

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu118
• Datasets 2.10.1
• Tokenizers 0.13.3