peft safetensors llama axolotl generated_from_trainer base_model:codellama/CodeLlama-7b-hf license:llama2 4-bit bitsandbytes region:us
---
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: `0.3.0`
```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: mlabonne/Evol-Instruct-Python-1k
    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: 0.3797

## 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: bitsandbytes
- 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

### 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3472        | 0.01  | 1    | 0.4986          |
| 0.3139        | 0.03  | 4    | 0.4985          |
| 0.2981        | 0.07  | 8    | 0.4983          |
| 0.4311        | 0.1   | 12   | 0.4979          |
| 0.3958        | 0.14  | 16   | 0.4960          |
| 0.335         | 0.17  | 20   | 0.4915          |
| 0.4286        | 0.2   | 24   | 0.4808          |
| 0.4011        | 0.24  | 28   | 0.4629          |
| 0.3269        | 0.27  | 32   | 0.4445          |
| 0.2559        | 0.31  | 36   | 0.4284          |
| 0.3786        | 0.34  | 40   | 0.4174          |
| 0.2967        | 0.37  | 44   | 0.4107          |
| 0.2677        | 0.41  | 48   | 0.4027          |
| 0.2455        | 0.44  | 52   | 0.3959          |
| 0.3267        | 0.47  | 56   | 0.3916          |
| 0.2902        | 0.51  | 60   | 0.3882          |
| 0.1845        | 0.54  | 64   | 0.3878          |
| 0.2593        | 0.58  | 68   | 0.3869          |
| 0.3104        | 0.61  | 72   | 0.3836          |
| 0.3799        | 0.64  | 76   | 0.3819          |
| 0.2059        | 0.68  | 80   | 0.3794          |
| 0.3177        | 0.71  | 84   | 0.3792          |
| 0.2307        | 0.75  | 88   | 0.3768          |
| 0.282         | 0.78  | 92   | 0.3749          |
| 0.2713        | 0.81  | 96   | 0.3738          |
| 0.2948        | 0.85  | 100  | 0.3725          |
| 0.2311        | 0.88  | 104  | 0.3713          |
| 0.2516        | 0.92  | 108  | 0.3716          |
| 0.2462        | 0.95  | 112  | 0.3715          |
| 0.2035        | 0.98  | 116  | 0.3711          |
| 0.2638        | 1.02  | 120  | 0.3712          |
| 0.2477        | 1.05  | 124  | 0.3726          |
| 0.1986        | 1.08  | 128  | 0.3682          |
| 0.2292        | 1.12  | 132  | 0.3671          |
| 0.1549        | 1.15  | 136  | 0.3680          |
| 0.1953        | 1.19  | 140  | 0.3683          |
| 0.224         | 1.22  | 144  | 0.3671          |
| 0.1941        | 1.25  | 148  | 0.3687          |
| 0.2234        | 1.29  | 152  | 0.3709          |
| 0.2659        | 1.32  | 156  | 0.3700          |
| 0.2535        | 1.36  | 160  | 0.3689          |
| 0.2115        | 1.39  | 164  | 0.3683          |
| 0.2481        | 1.42  | 168  | 0.3693          |
| 0.2101        | 1.46  | 172  | 0.3699          |
| 0.228         | 1.49  | 176  | 0.3697          |
| 0.3159        | 1.53  | 180  | 0.3680          |
| 0.2257        | 1.56  | 184  | 0.3664          |
| 0.1684        | 1.59  | 188  | 0.3670          |
| 0.2277        | 1.63  | 192  | 0.3663          |
| 0.2787        | 1.66  | 196  | 0.3668          |
| 0.2284        | 1.69  | 200  | 0.3654          |
| 0.2789        | 1.73  | 204  | 0.3640          |
| 0.2089        | 1.76  | 208  | 0.3632          |
| 0.3387        | 1.8   | 212  | 0.3633          |
| 0.2677        | 1.83  | 216  | 0.3610          |
| 0.2684        | 1.86  | 220  | 0.3609          |
| 0.2458        | 1.9   | 224  | 0.3610          |
| 0.2808        | 1.93  | 228  | 0.3602          |
| 0.2895        | 1.97  | 232  | 0.3596          |
| 0.323         | 2.0   | 236  | 0.3591          |
| 0.2105        | 2.03  | 240  | 0.3623          |
| 0.1911        | 2.07  | 244  | 0.3720          |
| 0.2888        | 2.1   | 248  | 0.3802          |
| 0.1958        | 2.13  | 252  | 0.3748          |
| 0.1785        | 2.17  | 256  | 0.3701          |
| 0.2604        | 2.2   | 260  | 0.3709          |
| 0.2212        | 2.24  | 264  | 0.3737          |
| 0.1996        | 2.27  | 268  | 0.3772          |
| 0.1567        | 2.3   | 272  | 0.3778          |
| 0.1777        | 2.34  | 276  | 0.3778          |
| 0.2642        | 2.37  | 280  | 0.3785          |
| 0.1907        | 2.4   | 284  | 0.3796          |
| 0.1637        | 2.44  | 288  | 0.3785          |
| 0.1778        | 2.47  | 292  | 0.3785          |
| 0.144         | 2.51  | 296  | 0.3789          |
| 0.1758        | 2.54  | 300  | 0.3788          |
| 0.2018        | 2.57  | 304  | 0.3784          |
| 0.3126        | 2.61  | 308  | 0.3783          |
| 0.1623        | 2.64  | 312  | 0.3790          |
| 0.223         | 2.68  | 316  | 0.3798          |
| 0.2109        | 2.71  | 320  | 0.3797          |
| 0.1606        | 2.74  | 324  | 0.3797          |
| 0.2226        | 2.78  | 328  | 0.3796          |
| 0.2068        | 2.81  | 332  | 0.3798          |
| 0.1547        | 2.85  | 336  | 0.3797          |
| 0.2513        | 2.88  | 340  | 0.3796          |
| 0.2688        | 2.91  | 344  | 0.3797          |
| 0.1481        | 2.95  | 348  | 0.3796          |
| 0.1443        | 2.98  | 352  | 0.3797          |


### Framework versions

- PEFT 0.7.0
- Transformers 4.37.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0