---
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-no-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-no-name-ft/train/train/train-conditionnestack2e-no-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-no-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-no-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: 0.4931

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8379        | 0.01  | 1    | 1.0354          |
| 0.3779        | 0.16  | 20   | 0.4820          |
| 0.3361        | 0.31  | 40   | 0.4560          |
| 0.3153        | 0.47  | 60   | 0.4467          |
| 0.2735        | 0.63  | 80   | 0.4457          |
| 0.2437        | 0.78  | 100  | 0.4400          |
| 0.2941        | 0.94  | 120  | 0.4416          |
| 0.2153        | 1.08  | 140  | 0.4466          |
| 0.2583        | 1.23  | 160  | 0.4499          |
| 0.2026        | 1.39  | 180  | 0.4540          |
| 0.185         | 1.55  | 200  | 0.4541          |
| 0.2296        | 1.7   | 220  | 0.4604          |
| 0.2059        | 1.86  | 240  | 0.4591          |
| 0.1998        | 2.02  | 260  | 0.4626          |
| 0.1879        | 2.15  | 280  | 0.4828          |
| 0.1861        | 2.31  | 300  | 0.4944          |
| 0.1561        | 2.47  | 320  | 0.4947          |
| 0.1888        | 2.62  | 340  | 0.4939          |
| 0.1665        | 2.78  | 360  | 0.4945          |
| 0.1627        | 2.94  | 380  | 0.4931          |


### Framework versions

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