---
library_name: peft
base_model: NousResearch/CodeLlama-7b-hf-flash
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 9fe7fc96-6a8c-4ab3-ba1e-77f1980fb606
  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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml
adapter: lora
auto_find_batch_size: true
base_model: NousResearch/CodeLlama-7b-hf-flash
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 6fa3d5264c24b5f4_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/6fa3d5264c24b5f4_train_data.json
  type:
    field_input: my_solu
    field_instruction: prompt
    field_output: solution
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
do_eval: true
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 50
evals_per_epoch: null
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: false
group_by_length: true
hub_model_id: lesso04/9fe7fc96-6a8c-4ab3-ba1e-77f1980fb606
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.000204
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 10
lora_alpha: 128
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 500
micro_batch_size: 4
mlflow_experiment_name: /tmp/G.O.D/6fa3d5264c24b5f4_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 50
saves_per_epoch: null
sequence_len: 512
special_tokens:
  pad_token: </s>
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 1e1aba89-0560-407f-87c7-7610230f4d86
wandb_project: 04a
wandb_run: your_name
wandb_runid: 1e1aba89-0560-407f-87c7-7610230f4d86
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 9fe7fc96-6a8c-4ab3-ba1e-77f1980fb606

This model is a fine-tuned version of [NousResearch/CodeLlama-7b-hf-flash](https://huggingface.co/NousResearch/CodeLlama-7b-hf-flash) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6941

## 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: 0.000204
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0001 | 1    | 1.1523          |
| 2.1069        | 0.0036 | 50   | 0.9481          |
| 1.8486        | 0.0071 | 100  | 0.8498          |
| 1.6075        | 0.0107 | 150  | 0.8301          |
| 1.7282        | 0.0143 | 200  | 0.7920          |
| 1.6895        | 0.0179 | 250  | 0.7721          |
| 1.678         | 0.0214 | 300  | 0.7368          |
| 1.5436        | 0.0250 | 350  | 0.7127          |
| 1.5503        | 0.0286 | 400  | 0.7006          |
| 1.5577        | 0.0322 | 450  | 0.6951          |
| 1.643         | 0.0357 | 500  | 0.6941          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1