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--- |
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library_name: peft |
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tags: |
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- axolotl |
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- generated_from_trainer |
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base_model: NousResearch/Llama-2-7b-hf |
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model-index: |
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- name: MathLlama-7b |
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results: [] |
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--- |
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Edit - Retraining model messed up the output. Maybe cz of my chat template. I will fine tune and update this. Stay Tuned :) |
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axolotl version: `0.3.0` |
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```yaml |
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base_model: NousResearch/Llama-2-7b-hf |
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model_type: LlamaForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_llama_derived_model: true |
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hub_model_id: MathLlama-7b |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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datasets: |
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- path: zorooo/Eval_Math_Derivatives |
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type: alpaca |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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output_dir: ./qlora-out-2 |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 2048 |
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sample_packing: true |
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pad_to_sequence_len: true |
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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_modules: |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: axolotl_run_1_math_llama |
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wandb_entity: |
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wandb_watch: |
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wandb_name: math_llama_run2 |
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wandb_log_model: |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 5 |
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optimizer: paged_adamw_32bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: true |
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fp16: false |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 100 |
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evals_per_epoch: 4 |
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eval_table_size: |
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saves_per_epoch: 1 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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bos_token: "<s>" |
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eos_token: "</s>" |
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unk_token: "<unk>" |
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``` |
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</details><br> |
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# MathLlama-7b |
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This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1702 |
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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: 0.0002 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.1242 | 0.04 | 1 | 0.1574 | |
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| 0.1265 | 0.27 | 7 | 0.1573 | |
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| 0.1644 | 0.54 | 14 | 0.1574 | |
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| 0.1213 | 0.82 | 21 | 0.1566 | |
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| 0.1219 | 1.06 | 28 | 0.1560 | |
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| 0.111 | 1.33 | 35 | 0.1577 | |
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| 0.1289 | 1.6 | 42 | 0.1562 | |
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| 0.1241 | 1.87 | 49 | 0.1551 | |
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| 0.1254 | 2.12 | 56 | 0.1592 | |
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| 0.1376 | 2.39 | 63 | 0.1646 | |
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| 0.132 | 2.66 | 70 | 0.1611 | |
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| 0.1165 | 2.93 | 77 | 0.1568 | |
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| 0.1047 | 3.18 | 84 | 0.1698 | |
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| 0.0918 | 3.46 | 91 | 0.1717 | |
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| 0.1022 | 3.73 | 98 | 0.1677 | |
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| 0.1136 | 4.0 | 105 | 0.1661 | |
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| 0.0856 | 4.25 | 112 | 0.1733 | |
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| 0.0834 | 4.52 | 119 | 0.1702 | |
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### Framework versions |
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- PEFT 0.7.2.dev0 |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
