---
license: llama2
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: codellama/CodeLlama-7b-hf
model-index:
- name: EvolCodeLlama-JS-7b
results: []
---
[
](https://github.com/OpenAccess-AI-Collective/axolotl)
See axolotl config
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-JS-7b
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: harryng4869/Evol-Instruct-JS-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: ""
eos_token: ""
unk_token: ""
```
# EvolCodeLlama-JS-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: 0.2897
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4099 | 0.02 | 1 | 0.4313 |
| 0.5677 | 0.04 | 2 | 0.4313 |
| 0.4255 | 0.08 | 4 | 0.4315 |
| 0.4352 | 0.12 | 6 | 0.4312 |
| 0.4457 | 0.17 | 8 | 0.4312 |
| 0.4705 | 0.21 | 10 | 0.4309 |
| 0.4492 | 0.25 | 12 | 0.4303 |
| 0.5233 | 0.29 | 14 | 0.4294 |
| 0.3795 | 0.33 | 16 | 0.4275 |
| 0.456 | 0.37 | 18 | 0.4248 |
| 0.5132 | 0.41 | 20 | 0.4204 |
| 0.3543 | 0.46 | 22 | 0.4136 |
| 0.4132 | 0.5 | 24 | 0.4046 |
| 0.4219 | 0.54 | 26 | 0.3936 |
| 0.3956 | 0.58 | 28 | 0.3813 |
| 0.3587 | 0.62 | 30 | 0.3697 |
| 0.409 | 0.66 | 32 | 0.3587 |
| 0.3093 | 0.7 | 34 | 0.3483 |
| 0.3717 | 0.75 | 36 | 0.3407 |
| 0.3357 | 0.79 | 38 | 0.3345 |
| 0.2912 | 0.83 | 40 | 0.3289 |
| 0.3171 | 0.87 | 42 | 0.3243 |
| 0.3368 | 0.91 | 44 | 0.3210 |
| 0.3906 | 0.95 | 46 | 0.3180 |
| 0.3491 | 0.99 | 48 | 0.3159 |
| 0.274 | 1.02 | 50 | 0.3133 |
| 0.2474 | 1.06 | 52 | 0.3126 |
| 0.3236 | 1.1 | 54 | 0.3106 |
| 0.3327 | 1.14 | 56 | 0.3092 |
| 0.3153 | 1.18 | 58 | 0.3081 |
| 0.3809 | 1.22 | 60 | 0.3079 |
| 0.2792 | 1.26 | 62 | 0.3072 |
| 0.2465 | 1.31 | 64 | 0.3055 |
| 0.2831 | 1.35 | 66 | 0.3060 |
| 0.408 | 1.39 | 68 | 0.3064 |
| 0.2881 | 1.43 | 70 | 0.3045 |
| 0.2715 | 1.47 | 72 | 0.3018 |
| 0.2686 | 1.51 | 74 | 0.3008 |
| 0.3605 | 1.55 | 76 | 0.3008 |
| 0.2644 | 1.6 | 78 | 0.3002 |
| 0.3479 | 1.64 | 80 | 0.2990 |
| 0.2821 | 1.68 | 82 | 0.2983 |
| 0.3193 | 1.72 | 84 | 0.2980 |
| 0.2857 | 1.76 | 86 | 0.2969 |
| 0.2484 | 1.8 | 88 | 0.2965 |
| 0.236 | 1.84 | 90 | 0.2957 |
| 0.3554 | 1.89 | 92 | 0.2946 |
| 0.2968 | 1.93 | 94 | 0.2931 |
| 0.3792 | 1.97 | 96 | 0.2914 |
| 0.2574 | 2.01 | 98 | 0.2909 |
| 0.3192 | 2.02 | 100 | 0.2915 |
| 0.2519 | 2.06 | 102 | 0.2934 |
| 0.2165 | 2.1 | 104 | 0.2968 |
| 0.2499 | 2.14 | 106 | 0.2960 |
| 0.2243 | 2.18 | 108 | 0.2931 |
| 0.2523 | 2.22 | 110 | 0.2923 |
| 0.2644 | 2.26 | 112 | 0.2943 |
| 0.2048 | 2.31 | 114 | 0.2946 |
| 0.1853 | 2.35 | 116 | 0.2932 |
| 0.2441 | 2.39 | 118 | 0.2927 |
| 0.2494 | 2.43 | 120 | 0.2928 |
| 0.2184 | 2.47 | 122 | 0.2927 |
| 0.2376 | 2.51 | 124 | 0.2932 |
| 0.2496 | 2.55 | 126 | 0.2924 |
| 0.2029 | 2.6 | 128 | 0.2915 |
| 0.2602 | 2.64 | 130 | 0.2908 |
| 0.2137 | 2.68 | 132 | 0.2907 |
| 0.2617 | 2.72 | 134 | 0.2901 |
| 0.2532 | 2.76 | 136 | 0.2901 |
| 0.2743 | 2.8 | 138 | 0.2900 |
| 0.2181 | 2.84 | 140 | 0.2900 |
| 0.254 | 2.89 | 142 | 0.2899 |
| 0.2463 | 2.93 | 144 | 0.2897 |
### Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0