---
license: llama2
base_model: codellama/CodeLlama-7b-hf
tags:
- generated_from_trainer
model-index:
- name: autofix10k
  results: []
library_name: peft
---

<!-- 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. -->

# autofix10k

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: 0.4372

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: QuantizationMethod.BITS_AND_BYTES
- _load_in_8bit: True
- _load_in_4bit: False
- 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: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
- bnb_4bit_quant_storage: uint8
- load_in_4bit: False
- load_in_8bit: True
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7922        | 0.2   | 20   | 0.5237          |
| 0.5053        | 0.4   | 40   | 0.4857          |
| 0.4071        | 0.6   | 60   | 0.4356          |
| 0.4297        | 0.8   | 80   | 0.4154          |
| 0.5313        | 1.0   | 100  | 0.3827          |
| 0.4814        | 1.2   | 120  | 0.3785          |
| 0.3739        | 1.4   | 140  | 0.3774          |
| 0.3279        | 1.6   | 160  | 0.3761          |
| 0.3149        | 1.8   | 180  | 0.3732          |
| 0.4086        | 2.0   | 200  | 0.3658          |
| 0.3724        | 2.2   | 220  | 0.3664          |
| 0.3691        | 2.4   | 240  | 0.3644          |
| 0.3065        | 2.6   | 260  | 0.3679          |
| 0.2688        | 2.8   | 280  | 0.3767          |
| 0.3431        | 3.0   | 300  | 0.3633          |
| 0.333         | 3.2   | 320  | 0.3641          |
| 0.3052        | 3.4   | 340  | 0.3597          |
| 0.2444        | 3.6   | 360  | 0.3779          |
| 0.2455        | 3.8   | 380  | 0.3712          |
| 0.3078        | 4.0   | 400  | 0.3578          |
| 0.2877        | 4.2   | 420  | 0.3650          |
| 0.2659        | 4.4   | 440  | 0.3731          |
| 0.2496        | 4.6   | 460  | 0.3764          |
| 0.218         | 4.8   | 480  | 0.3781          |
| 0.219         | 5.0   | 500  | 0.3742          |
| 0.2119        | 5.2   | 520  | 0.3808          |
| 0.2435        | 5.4   | 540  | 0.3871          |
| 0.2331        | 5.6   | 560  | 0.3818          |
| 0.1738        | 5.8   | 580  | 0.3758          |
| 0.1772        | 6.0   | 600  | 0.3731          |
| 0.1607        | 6.2   | 620  | 0.4121          |
| 0.1942        | 6.4   | 640  | 0.3943          |
| 0.2312        | 6.6   | 660  | 0.3867          |
| 0.1528        | 6.8   | 680  | 0.4160          |
| 0.1155        | 7.0   | 700  | 0.4100          |
| 0.1495        | 7.2   | 720  | 0.4081          |
| 0.1674        | 7.4   | 740  | 0.4015          |
| 0.1849        | 7.6   | 760  | 0.4075          |
| 0.1231        | 7.8   | 780  | 0.4238          |
| 0.0905        | 8.0   | 800  | 0.4128          |
| 0.1156        | 8.2   | 820  | 0.4278          |
| 0.1628        | 8.4   | 840  | 0.4203          |
| 0.1545        | 8.6   | 860  | 0.4219          |
| 0.1236        | 8.8   | 880  | 0.4294          |
| 0.0799        | 9.0   | 900  | 0.4224          |
| 0.0991        | 9.2   | 920  | 0.4399          |
| 0.1176        | 9.4   | 940  | 0.4350          |
| 0.1711        | 9.6   | 960  | 0.4362          |
| 0.1106        | 9.8   | 980  | 0.4414          |
| 0.0582        | 10.0  | 1000 | 0.4372          |


### Framework versions

- PEFT 0.4.0
- Transformers 4.40.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2