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---
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 |