| --- |
| license: other |
| library_name: peft |
| tags: |
| - generated_from_trainer |
| base_model: intervitens/internlm2-limarp-chat-20b |
| model-index: |
| - name: outputs/qlora-out |
| 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. --> |
| Compute power from g4rg. Big Thanks. |
|
|
| [<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 |
| mlflow_tracking_uri: http://127.0.0.1:2340 |
| mlflow_experiment_name: Default |
| |
| base_model: intervitens/internlm2-limarp-chat-20b |
| model_type: AutoModelForCausalLM |
| tokenizer_type: AutoTokenizer |
| |
| load_in_8bit: false |
| load_in_4bit: true |
| strict: false |
| |
| datasets: |
| - path: ResplendentAI/Alpaca_NSFW_Shuffled |
| type: alpaca |
| - path: diffnamehard/toxic-dpo-v0.1-NoWarning-alpaca |
| type: alpaca |
| dataset_prepared_path: last_run_prepared |
| val_set_size: 0.1 |
| output_dir: ./outputs/qlora-out |
| |
| adapter: qlora |
| lora_model_dir: |
| |
| sequence_len: 8192 |
| sample_packing: false |
| pad_to_sequence_len: true |
| |
| lora_r: 32 |
| lora_alpha: 16 |
| lora_dropout: 0.05 |
| lora_target_linear: true |
| lora_fan_in_fan_out: |
| lora_target_modules: |
| - gate_proj |
| - down_proj |
| - up_proj |
| - q_proj |
| - v_proj |
| - k_proj |
| - o_proj |
| |
| wandb_project: |
| wandb_entity: |
| wandb_watch: |
| wandb_name: |
| wandb_log_model: |
| |
| gradient_accumulation_steps: 4 |
| micro_batch_size: 2 |
| num_epochs: 4 |
| optimizer: adamw_bnb_8bit |
| lr_scheduler: cosine |
| learning_rate: 0.0002 |
| |
| train_on_inputs: false |
| group_by_length: false |
| bf16: auto |
| fp16: |
| tf32: false |
| |
| gradient_checkpointing: true |
| early_stopping_patience: |
| resume_from_checkpoint: |
| local_rank: |
| logging_steps: 1 |
| xformers_attention: |
| flash_attention: true |
| |
| loss_watchdog_threshold: 5.0 |
| loss_watchdog_patience: 3 |
| |
| warmup_steps: 10 |
| evals_per_epoch: 4 |
| eval_table_size: |
| eval_max_new_tokens: 128 |
| saves_per_epoch: 1 |
| debug: |
| deepspeed: |
| weight_decay: 0.0 |
| fsdp: |
| fsdp_config: |
| special_tokens: |
| |
| ``` |
|
|
| </details><br> |
|
|
| # outputs/qlora-out |
|
|
| This model is a fine-tuned version of [intervitens/internlm2-limarp-chat-20b](https://huggingface.co/intervitens/internlm2-limarp-chat-20b) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9896 |
|
|
| ## 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: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 7 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 56 |
| - total_eval_batch_size: 14 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 10 |
| - num_epochs: 4 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 1.4668 | 0.0476 | 1 | 1.4615 | |
| | 1.3541 | 0.2857 | 6 | 1.4253 | |
| | 1.2057 | 0.5714 | 12 | 1.2120 | |
| | 1.0818 | 0.8571 | 18 | 1.1259 | |
| | 1.0835 | 1.1429 | 24 | 1.0750 | |
| | 1.0503 | 1.4286 | 30 | 1.0451 | |
| | 1.0031 | 1.7143 | 36 | 1.0288 | |
| | 0.9728 | 2.0 | 42 | 1.0137 | |
| | 0.8879 | 2.2857 | 48 | 1.0082 | |
| | 0.8981 | 2.5714 | 54 | 0.9956 | |
| | 0.8613 | 2.8571 | 60 | 0.9926 | |
| | 0.8608 | 3.1429 | 66 | 0.9903 | |
| | 0.7841 | 3.4286 | 72 | 0.9903 | |
| | 0.9237 | 3.7143 | 78 | 0.9899 | |
| | 0.868 | 4.0 | 84 | 0.9896 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.10.0 |
| - Transformers 4.40.2 |
| - Pytorch 2.3.0 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
