| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: 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. --> |
|
|
| [<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: `0.3.0` |
| ```yaml |
| base_model: out/ |
| model_type: MistralForCausalLM |
| tokenizer_type: LlamaTokenizer |
| is_mistral_derived_model: true |
| |
| load_in_8bit: false |
| load_in_4bit: false |
| strict: false |
| |
| datasets: |
| - path: cognitivecomputations/leet10k-alpaca |
| type: alpaca |
| dataset_prepared_path: |
| val_set_size: 0.05 |
| output_dir: ./out |
| |
| sequence_len: 8192 |
| sample_packing: true |
| pad_to_sequence_len: true |
| eval_sample_packing: false |
| |
| wandb_project: |
| wandb_entity: |
| wandb_watch: |
| wandb_name: |
| wandb_log_model: |
| |
| gradient_accumulation_steps: 4 |
| micro_batch_size: 2 |
| num_epochs: 1 |
| optimizer: adamw_bnb_8bit |
| lr_scheduler: cosine |
| learning_rate: 0.000005 |
| |
| train_on_inputs: false |
| group_by_length: false |
| bf16: true |
| fp16: false |
| tf32: false |
| |
| gradient_checkpointing: true |
| early_stopping_patience: |
| resume_from_checkpoint: |
| local_rank: |
| logging_steps: 1 |
| xformers_attention: |
| flash_attention: true |
| |
| warmup_steps: 10 |
| evals_per_epoch: 4 |
| eval_table_size: |
| eval_table_max_new_tokens: 128 |
| saves_per_epoch: 1 |
| debug: |
| deepspeed: |
| weight_decay: 0.0 |
| fsdp: |
| fsdp_config: |
| special_tokens: |
| bos_token: "<s>" |
| eos_token: "</s>" |
| unk_token: "<unk>" |
| |
| ``` |
|
|
| </details><br> |
|
|
| # out |
|
|
| This model was trained from scratch on the /leet10k-alpaca dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5907 |
|
|
| ## 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: 5e-06 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 8 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 10 |
| - num_epochs: 1 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 0.7842 | 0.01 | 1 | 0.8053 | |
| | 0.5057 | 0.26 | 35 | 0.5694 | |
| | 0.3987 | 0.51 | 70 | 0.5752 | |
| | 0.2964 | 0.77 | 105 | 0.5907 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.37.0.dev0 |
| - Pytorch 2.0.1+cu117 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.0 |
|
|
| # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
| Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_NovoCode__Novocode7b-v2) |
|
|
| | Metric |Value| |
| |---------------------------------|----:| |
| |Avg. |56.57| |
| |AI2 Reasoning Challenge (25-Shot)|61.01| |
| |HellaSwag (10-Shot) |84.12| |
| |MMLU (5-Shot) |64.05| |
| |TruthfulQA (0-shot) |42.21| |
| |Winogrande (5-shot) |79.87| |
| |GSM8k (5-shot) | 8.19| |
|
|
|
|
