andstor/meta-llama-CodeLlama-7b-hf-unit-test-fine-tuning

output

This model is a fine-tuned version of meta-llama/CodeLlama-7b-hf on the fals3/methods2test_small fm+fc+c+m+f+t+tc dataset. It achieves the following results on the evaluation set:

• Loss: 0.5437
• Accuracy: 0.6745

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: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• total_eval_batch_size: 2
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3.0

Training results

Framework versions

• Transformers 4.41.0.dev0
• Pytorch 2.2.1+cu118
• Datasets 2.17.1
• Tokenizers 0.19.1