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---
license: llama2
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: codellama/CodeLlama-7b-hf
model-index:
- name: codellama-7b-text-to-sql
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# codellama-7b-text-to-sql
This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4224
- Rouge Scores: {'rouge1': 0.9523274691414706, 'rouge2': 0.8974742261714255, 'rougeL': 0.9171288478946306, 'rougeLsum': 0.9523427810006704}
- Bleu Scores: [0.9655707421980068, 0.9566701190306537, 0.9459215028465041, 0.9346533822146271]
- Gen Len: 138.6233
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge Scores | Bleu Scores | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:--------:|
| 0.4229 | 1.0 | 4800 | 0.4162 | {'rouge1': 0.9506510098188024, 'rouge2': 0.8949972495187106, 'rougeL': 0.9142255494550289, 'rougeLsum': 0.9506551339456668} | [0.9637759028147137, 0.9546609970402782, 0.9437656479747901, 0.9323669423057117] | 138.6233 |
| 0.3314 | 2.0 | 9600 | 0.4004 | {'rouge1': 0.9524326989909003, 'rouge2': 0.8987509624898048, 'rougeL': 0.9179414410323365, 'rougeLsum': 0.9524550499725172} | [0.9652102001679345, 0.9563139443363083, 0.9456856232691524, 0.9345677892198804] | 138.6233 |
| 0.2666 | 3.0 | 14400 | 0.4224 | {'rouge1': 0.9523274691414706, 'rouge2': 0.8974742261714255, 'rougeL': 0.9171288478946306, 'rougeLsum': 0.9523427810006704} | [0.9655707421980068, 0.9566701190306537, 0.9459215028465041, 0.9346533822146271] | 138.6233 |
### Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2 |