| --- |
| 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 |
