evaluation_model

This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.7124
• Accuracy: 0.4667
• Precision: 0.4577
• Recall: 0.9559
• F1: 0.6190

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: 5e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• 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
• lr_scheduler_warmup_steps: 500
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	0.9829	43	0.9195	0.5467	0.0	0.0	0.0
No log	1.9943	87	0.6833	0.5667	0.5172	0.6618	0.5806
No log	2.9829	130	0.6898	0.5267	0.4884	0.9265	0.6396
0.8708	3.9943	174	0.6775	0.5667	0.5149	0.7647	0.6154
0.8708	4.9371	215	0.7124	0.4667	0.4577	0.9559	0.6190

Framework versions

• PEFT 0.13.2
• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3