Finetuning Llama-7b on text-to-sql task
This model is a fine-tuned version of codellama/CodeLlama-7b-hf on b-mc2/sql-create-context.
Training and evaluation data
The model is trained on 10,000 random samples from b-mc2/sql-create-context. It is trained in a manner described by Phil Schmid here.
Training hyperparameters
Hyperparameter | Value |
---|---|
learning_rate | 0.0002 |
train_batch_size | 50 |
eval_batch_size | 8 |
seed | 42 |
gradient_accumulation_steps | 2 |
total_train_batch_size | 100 |
optimizer | Adam with betas=(0.9,0.999) and epsilon=1e-08 |
lr_scheduler_type | constant |
lr_scheduler_warmup_ratio | 0.03 |
num_epochs | 3 |
Training results
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
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Model tree for pratikdoshi/finetune-llama-7b-text-to-sql
Base model
codellama/CodeLlama-7b-hf