---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: codellama/CodeLlama-13b-Instruct-hf
model-index:
- name: stg-cli13b-t7-cdp-ca.dt.hlms.cln.inter-b4s1e1-20240102-0727
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# stg-cli13b-t7-cdp-ca.dt.hlms.cln.inter-b4s1e1-20240102-0727

This model is a fine-tuned version of [codellama/CodeLlama-13b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0656

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4007        | 0.02  | 100  | 0.0985          |
| 0.0888        | 0.04  | 200  | 0.0823          |
| 0.0834        | 0.05  | 300  | 0.0800          |
| 0.0783        | 0.07  | 400  | 0.0799          |
| 0.0782        | 0.09  | 500  | 0.0755          |
| 0.0798        | 0.11  | 600  | 0.0771          |
| 0.077         | 0.13  | 700  | 0.0734          |
| 0.0747        | 0.14  | 800  | 0.0745          |
| 0.076         | 0.16  | 900  | 0.0727          |
| 0.0791        | 0.18  | 1000 | 0.0775          |
| 0.0752        | 0.2   | 1100 | 0.0717          |
| 0.0721        | 0.22  | 1200 | 0.0729          |
| 0.0731        | 0.23  | 1300 | 0.0710          |
| 0.0832        | 0.25  | 1400 | 0.0727          |
| 0.0722        | 0.27  | 1500 | 0.0715          |
| 0.0738        | 0.29  | 1600 | 0.0715          |
| 0.071         | 0.31  | 1700 | 0.0705          |
| 0.0738        | 0.32  | 1800 | 0.0713          |
| 0.075         | 0.34  | 1900 | 0.0710          |
| 0.0732        | 0.36  | 2000 | 0.0703          |
| 0.0712        | 0.38  | 2100 | 0.0701          |
| 0.0702        | 0.4   | 2200 | 0.0699          |
| 0.0733        | 0.41  | 2300 | 0.0697          |
| 0.0739        | 0.43  | 2400 | 0.0691          |
| 0.0688        | 0.45  | 2500 | 0.0684          |
| 0.0692        | 0.47  | 2600 | 0.0689          |
| 0.0727        | 0.49  | 2700 | 0.0690          |
| 0.073         | 0.5   | 2800 | 0.0685          |
| 0.0752        | 0.52  | 2900 | 0.0691          |
| 0.0696        | 0.54  | 3000 | 0.0681          |
| 0.0708        | 0.56  | 3100 | 0.0684          |
| 0.072         | 0.58  | 3200 | 0.0681          |
| 0.0716        | 0.59  | 3300 | 0.0689          |
| 0.0723        | 0.61  | 3400 | 0.0678          |
| 0.0678        | 0.63  | 3500 | 0.0676          |
| 0.0695        | 0.65  | 3600 | 0.0672          |
| 0.0689        | 0.67  | 3700 | 0.0676          |
| 0.0716        | 0.68  | 3800 | 0.0671          |
| 0.07          | 0.7   | 3900 | 0.0667          |
| 0.0683        | 0.72  | 4000 | 0.0665          |
| 0.0704        | 0.74  | 4100 | 0.0664          |
| 0.0702        | 0.76  | 4200 | 0.0665          |
| 0.0678        | 0.77  | 4300 | 0.0662          |
| 0.0679        | 0.79  | 4400 | 0.0661          |
| 0.069         | 0.81  | 4500 | 0.0660          |
| 0.0675        | 0.83  | 4600 | 0.0661          |
| 0.0682        | 0.85  | 4700 | 0.0660          |
| 0.0697        | 0.86  | 4800 | 0.0659          |
| 0.0689        | 0.88  | 4900 | 0.0658          |
| 0.0665        | 0.9   | 5000 | 0.0658          |
| 0.067         | 0.92  | 5100 | 0.0657          |
| 0.0666        | 0.94  | 5200 | 0.0657          |
| 0.0704        | 0.95  | 5300 | 0.0656          |
| 0.0682        | 0.97  | 5400 | 0.0656          |
| 0.0663        | 0.99  | 5500 | 0.0656          |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: QuantizationMethod.BITS_AND_BYTES
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16

### Framework versions


- PEFT 0.6.2