large-model-finetuned-code-alpaca

This model is a fine-tuned version of bigcode/large-model on the lewtun/code_alpaca dataset. It achieves the following results on the evaluation set:

• Loss: 1.1605

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: 2e-05
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 8
• total_train_batch_size: 64
• total_eval_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.03
• training_steps: 1

Training results

Training Loss	Epoch	Step	Validation Loss
1.1672	0.03	1	1.1605

Framework versions

• Transformers 4.28.1
• Pytorch 1.13.1+cu117
• Datasets 2.10.1
• Tokenizers 0.13.3