llama-2-7b-flash-attention2-lora-patent-classification

This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the patent-classification dataset. It achieves the following results on the evaluation set:

• Loss: 1.5598
• Accuracy: 0.436
• Precision Macro: 0.4276
• Recall Macro: 0.3658
• F1-score Macro: 0.3707

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: 0.0002
• train_batch_size: 4
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision Macro	Recall Macro	F1-score Macro
1.4059	1.0	6250	1.9046	0.3748	0.3815	0.3173	0.3012
1.1153	2.0	12500	1.6457	0.419	0.4162	0.3461	0.3466
1.0234	3.0	18750	1.5598	0.436	0.4276	0.3658	0.3707

Framework versions

• PEFT 0.7.2.dev0
• Transformers 4.37.0.dev0
• Pytorch 2.1.0+cu121
• Datasets 2.16.2.dev0
• Tokenizers 0.15.0