---
license: llama2
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: codellama/CodeLlama-7b-hf
model-index:
- name: EvolCodeLlama-7b
  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. -->

[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.0`
```yaml
base_model: codellama/CodeLlama-7b-hf
base_model_config: codellama/CodeLlama-7b-hf
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
is_llama_derived_model: true
hub_model_id: EvolCodeLlama-7b

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: ptoro/Evol-Instruct-Python-1k-testing
    type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.02
output_dir: ./qlora-out

adapter: qlora
lora_model_dir:

sequence_len: 2048
sample_packing: true

lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project: axolotl
wandb_entity:
wandb_watch:
wandb_run_id:
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 3
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 100
eval_steps: 0.01
save_strategy: epoch
save_steps:
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"
```

</details><br>

# EvolCodeLlama-7b

This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3828

## 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: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3627        | 0.01  | 1    | 0.5027          |
| 0.3412        | 0.03  | 4    | 0.5026          |
| 0.3806        | 0.07  | 8    | 0.5023          |
| 0.392         | 0.1   | 12   | 0.5018          |
| 0.4141        | 0.14  | 16   | 0.4999          |
| 0.3433        | 0.17  | 20   | 0.4954          |
| 0.3702        | 0.21  | 24   | 0.4851          |
| 0.2948        | 0.24  | 28   | 0.4682          |
| 0.3387        | 0.28  | 32   | 0.4499          |
| 0.2437        | 0.31  | 36   | 0.4331          |
| 0.2526        | 0.35  | 40   | 0.4221          |
| 0.2721        | 0.38  | 44   | 0.4146          |
| 0.2292        | 0.42  | 48   | 0.4089          |
| 0.1986        | 0.45  | 52   | 0.4028          |
| 0.3258        | 0.48  | 56   | 0.3983          |
| 0.3509        | 0.52  | 60   | 0.3950          |
| 0.2697        | 0.55  | 64   | 0.3926          |
| 0.2646        | 0.59  | 68   | 0.3907          |
| 0.3979        | 0.62  | 72   | 0.3900          |
| 0.2737        | 0.66  | 76   | 0.3880          |
| 0.2271        | 0.69  | 80   | 0.3865          |
| 0.247         | 0.73  | 84   | 0.3847          |
| 0.3112        | 0.76  | 88   | 0.3824          |
| 0.2724        | 0.8   | 92   | 0.3820          |
| 0.207         | 0.83  | 96   | 0.3814          |
| 0.3492        | 0.87  | 100  | 0.3810          |
| 0.2474        | 0.9   | 104  | 0.3802          |
| 0.4037        | 0.94  | 108  | 0.3785          |
| 0.2295        | 0.97  | 112  | 0.3773          |
| 0.2689        | 1.0   | 116  | 0.3760          |
| 0.2546        | 1.02  | 120  | 0.3753          |
| 0.1916        | 1.05  | 124  | 0.3768          |
| 0.2458        | 1.09  | 128  | 0.3758          |
| 0.2155        | 1.12  | 132  | 0.3768          |
| 0.2341        | 1.16  | 136  | 0.3773          |
| 0.1909        | 1.19  | 140  | 0.3793          |
| 0.1911        | 1.23  | 144  | 0.3759          |
| 0.2096        | 1.26  | 148  | 0.3761          |
| 0.2353        | 1.29  | 152  | 0.3772          |
| 0.2606        | 1.33  | 156  | 0.3773          |
| 0.1485        | 1.36  | 160  | 0.3778          |
| 0.1807        | 1.4   | 164  | 0.3749          |
| 0.2294        | 1.43  | 168  | 0.3770          |
| 0.216         | 1.47  | 172  | 0.3759          |
| 0.1791        | 1.5   | 176  | 0.3727          |
| 0.2605        | 1.54  | 180  | 0.3733          |
| 0.2838        | 1.57  | 184  | 0.3738          |
| 0.2632        | 1.61  | 188  | 0.3694          |
| 0.1839        | 1.64  | 192  | 0.3686          |
| 0.1939        | 1.68  | 196  | 0.3690          |
| 0.2413        | 1.71  | 200  | 0.3699          |
| 0.1494        | 1.74  | 204  | 0.3689          |
| 0.2782        | 1.78  | 208  | 0.3695          |
| 0.2314        | 1.81  | 212  | 0.3696          |
| 0.2499        | 1.85  | 216  | 0.3691          |
| 0.1976        | 1.88  | 220  | 0.3672          |
| 0.2587        | 1.92  | 224  | 0.3660          |
| 0.2598        | 1.95  | 228  | 0.3658          |
| 0.2686        | 1.99  | 232  | 0.3666          |
| 0.216         | 2.01  | 236  | 0.3673          |
| 0.1261        | 2.04  | 240  | 0.3723          |
| 0.1938        | 2.08  | 244  | 0.3811          |
| 0.1906        | 2.11  | 248  | 0.3869          |
| 0.1375        | 2.15  | 252  | 0.3829          |
| 0.228         | 2.18  | 256  | 0.3796          |
| 0.2524        | 2.22  | 260  | 0.3789          |
| 0.118         | 2.25  | 264  | 0.3809          |
| 0.2224        | 2.29  | 268  | 0.3834          |
| 0.1477        | 2.32  | 272  | 0.3847          |
| 0.2095        | 2.35  | 276  | 0.3849          |
| 0.1919        | 2.39  | 280  | 0.3820          |
| 0.1916        | 2.42  | 284  | 0.3804          |
| 0.1625        | 2.46  | 288  | 0.3788          |
| 0.2054        | 2.49  | 292  | 0.3794          |
| 0.1605        | 2.53  | 296  | 0.3810          |
| 0.1564        | 2.56  | 300  | 0.3819          |
| 0.196         | 2.6   | 304  | 0.3822          |
| 0.1975        | 2.63  | 308  | 0.3830          |
| 0.1406        | 2.67  | 312  | 0.3833          |
| 0.2754        | 2.7   | 316  | 0.3830          |
| 0.1544        | 2.74  | 320  | 0.3829          |
| 0.1733        | 2.77  | 324  | 0.3830          |
| 0.1862        | 2.81  | 328  | 0.3832          |
| 0.1634        | 2.84  | 332  | 0.3829          |
| 0.1966        | 2.87  | 336  | 0.3830          |
| 0.1306        | 2.91  | 340  | 0.3831          |
| 0.1444        | 2.94  | 344  | 0.3828          |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.37.0
- Pytorch 2.0.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0