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--- |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: /GenAI4HW/llama2_13b |
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metrics: |
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- accuracy |
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model-index: |
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- name: outputs/llama2-13B-lora-QuArch_0_1_1_alpaca_filtered-answer-context-test-new |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.0` |
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```yaml |
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## General |
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# base_model: meta-llama/Meta-Llama-3-8B-Instruct |
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base_model: /GenAI4HW/llama2_13b |
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# base_model: meta-llama/Llama-2-13b |
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model_type: LlamaForCausalLM |
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tokenizer_type: AutoTokenizer |
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# tokenizer_type: LlamaTokenizer |
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output_dir: ./outputs/llama2-13B-lora-QuArch_0_1_1_alpaca_filtered-answer-context-test-new |
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seed: 42 |
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## Data Configuration |
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datasets: |
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# - path: ./data/QuArch_v0_1_0_alpaca_w_context.json # With abstract |
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# - path: ./data/QuArch_v0_1_1_alpaca_format.json # With justification |
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# - path: ./data/QuArch_v0_1_0_alpaca_mmlu.json # Without justification |
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- path: ./data/QuArch_v0_1_1_alpaca_filtered_context/ |
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type: alpaca |
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data_file: train |
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dataset_prepared_path: |
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test_datasets: |
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- path: ./data/QuArch_v0_1_1_alpaca_filtered_context/ |
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type: alpaca |
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split: test |
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data_file: |
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- test |
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# - path: ./data/QuArch_v0_1_1_alpaca_filtered_context/ |
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# type: alpaca |
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# split: val |
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# data_file: |
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# - val |
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## Model Configuration |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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bf16: auto |
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fp16: |
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tf32: false |
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device_map: 'auto' |
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## LoRA Configuration |
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adapter: lora |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_model_dir: |
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lora_fan_in_fan_out: |
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## Logging Configuration |
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logging_dir: ./logs |
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logging_steps: 10 |
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wandb_project: |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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do_eval: true |
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## Training Configuration |
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sequence_len: 1024 |
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sample_packing: true |
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pad_to_sequence_len: true |
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train_on_inputs: false |
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group_by_length: false |
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micro_batch_size: 1 |
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gradient_accumulation_steps: 16 |
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num_epochs: 30 |
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warmup_steps: 10 |
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weight_decay: 0.01 |
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optimizer: adamw_torch |
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lr_scheduler: linear |
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learning_rate: 2e-5 |
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gradient_checkpointing: false |
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saves_per_epoch: 1 |
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# save_steps: 0 |
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# save_strategy: steps |
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save_total_limit: 30 |
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load_best_model_at_end: true |
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greater_is_better: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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remove_unused_columns: true |
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## Evaluation Configuration |
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eval_sample_packing: False |
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eval_batch_size: 1 |
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evals_per_epoch: 1 |
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# evaluation_strategy: epoch |
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eval_max_new_tokens: 32 |
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eval_table_size: |
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# max_new_token: 32 |
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# eval_causal_lm_metrics: sacrebleu |
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# Others |
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local_rank: |
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xformers_attention: |
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flash_attention: true |
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s2_attention: |
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debug: |
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deepspeed: |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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# pad_token: <|end_of_text|> |
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``` |
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</details><br> |
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# outputs/llama2-13B-lora-QuArch_0_1_1_alpaca_filtered-answer-context-test-new |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0432 |
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- Accuracy: 0.9808 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 2 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| No log | 0.2105 | 1 | 5.1322 | 0.6154 | |
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| No log | 0.8421 | 4 | 5.1271 | 0.6346 | |
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| No log | 1.6842 | 8 | 5.0601 | 0.6538 | |
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| 5.1323 | 2.5263 | 12 | 4.7743 | 0.7885 | |
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| 5.1323 | 3.3684 | 16 | 4.0491 | 0.9231 | |
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| 4.2735 | 4.2105 | 20 | 2.6444 | 0.8846 | |
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| 4.2735 | 5.0526 | 24 | 1.0551 | 0.9615 | |
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| 4.2735 | 5.8947 | 28 | 0.4698 | 0.6923 | |
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| 1.2232 | 6.7368 | 32 | 0.3224 | 0.6731 | |
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| 1.2232 | 7.5789 | 36 | 0.2527 | 1.0 | |
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| 0.3083 | 8.4211 | 40 | 0.1972 | 1.0 | |
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| 0.3083 | 9.2632 | 44 | 0.1372 | 0.9615 | |
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| 0.3083 | 10.1053 | 48 | 0.0803 | 1.0 | |
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| 0.1761 | 10.9474 | 52 | 0.0575 | 0.9808 | |
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| 0.1761 | 11.7895 | 56 | 0.0475 | 0.9808 | |
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| 0.116 | 12.6316 | 60 | 0.0444 | 0.9808 | |
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| 0.116 | 13.4737 | 64 | 0.0463 | 0.9808 | |
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| 0.116 | 14.3158 | 68 | 0.0489 | 0.9808 | |
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| 0.0814 | 15.1579 | 72 | 0.0495 | 0.9808 | |
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| 0.0814 | 16.0 | 76 | 0.0481 | 0.9808 | |
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| 0.0709 | 16.8421 | 80 | 0.0469 | 0.9808 | |
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| 0.0709 | 17.6842 | 84 | 0.0457 | 0.9808 | |
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| 0.0709 | 18.5263 | 88 | 0.0455 | 0.9808 | |
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| 0.0632 | 19.3684 | 92 | 0.0454 | 0.9808 | |
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| 0.0632 | 20.2105 | 96 | 0.0459 | 0.9808 | |
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| 0.0569 | 21.0526 | 100 | 0.0458 | 0.9808 | |
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| 0.0569 | 21.8947 | 104 | 0.0446 | 0.9808 | |
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| 0.0569 | 22.7368 | 108 | 0.0451 | 0.9808 | |
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| 0.055 | 23.5789 | 112 | 0.0446 | 0.9808 | |
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| 0.055 | 24.4211 | 116 | 0.0452 | 0.9808 | |
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| 0.0581 | 25.2632 | 120 | 0.0432 | 0.9808 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
