---
license: llama2
base_model: codellama/CodeLlama-7b-Instruct-hf
tags:
- generated_from_trainer
library_name: peft
model-index:
- name: work/10283/sarella/ls6/exlong-internal/_work/exp/conditionnestack2e-with-name-ft/lora-codellama-7b-123
  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
adapter: lora
base_model: codellama/CodeLlama-7b-Instruct-hf
base_model_config: codellama/CodeLlama-7b-Instruct-hf
bf16: true
dataset_prepared_path: null
datasets:
- path: /work/10283/sarella/ls6/exlong-internal/_work/setup/conditionnestack2e-with-name-ft/train/train/train-conditionnestack2e-with-name-ft.jsonl
  type:
    field_input: input
    field_instruction: instruction
    field_output: output
    field_system: system
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: You are a helpful programming assistant and an expert Java programmer.
      You are helping a user writing exceptional-behavior tests for their Java code.
debug: null
deepspeed: null
early_stopping_patience: null
eval_sample_packing: false
eval_steps: 20
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
is_llama_derived_model: true
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: true
local_rank: null
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
micro_batch_size: 4
model_type: LlamaForCausalLM
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: /work/10283/sarella/ls6/exlong-internal/_work/exp/conditionnestack2e-with-name-ft/lora-codellama-7b-123
pad_to_sequence_len: true
resume_from_checkpoint: null
sample_packing: true
save_steps: null
seed: 123
sequence_len: 4096
special_tokens:
  bos_token: <s>
  eos_token: </s>
  unk_token: <unk>
strict: false
tf32: false
tokenizer_type: CodeLlamaTokenizer
train_on_inputs: false
val_set_size: 0.01
wandb_entity: null
wandb_log_model: null
wandb_project: null
wandb_run_id: null
wandb_watch: null
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# work/10283/sarella/ls6/exlong-internal/_work/exp/conditionnestack2e-with-name-ft/lora-codellama-7b-123

This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2909

## 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: 4
- eval_batch_size: 4
- seed: 123
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.631         | 0.01  | 1    | 0.7976          |
| 0.2584        | 0.16  | 20   | 0.3000          |
| 0.2045        | 0.31  | 40   | 0.2802          |
| 0.1596        | 0.47  | 60   | 0.2725          |
| 0.2024        | 0.62  | 80   | 0.2715          |
| 0.1613        | 0.78  | 100  | 0.2638          |
| 0.1341        | 0.93  | 120  | 0.2638          |
| 0.1295        | 1.07  | 140  | 0.2672          |
| 0.122         | 1.22  | 160  | 0.2694          |
| 0.1247        | 1.38  | 180  | 0.2711          |
| 0.1344        | 1.53  | 200  | 0.2733          |
| 0.1329        | 1.69  | 220  | 0.2796          |
| 0.1095        | 1.85  | 240  | 0.2731          |
| 0.1167        | 2.0   | 260  | 0.2751          |
| 0.0929        | 2.14  | 280  | 0.2849          |
| 0.1112        | 2.3   | 300  | 0.2927          |
| 0.1132        | 2.45  | 320  | 0.2856          |
| 0.0876        | 2.61  | 340  | 0.2915          |
| 0.0982        | 2.76  | 360  | 0.2894          |
| 0.1042        | 2.92  | 380  | 0.2909          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.0