| --- |
| license: mit |
| library_name: peft |
| tags: |
| - generated_from_trainer |
| base_model: microsoft/phi-1_5 |
| model-index: |
| - name: phi-sft-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: `0.4.0` |
| ```yaml |
| base_model: microsoft/phi-1_5 |
| model_type: AutoModelForCausalLM |
| tokenizer_type: AutoTokenizer |
| |
| load_in_8bit: false |
| load_in_4bit: true |
| strict: false |
| |
| datasets: |
| - path: garage-bAInd/Open-Platypus |
| type: alpaca |
| |
| dataset_prepared_path: |
| val_set_size: 0.05 |
| output_dir: ./phi-sft-out |
| |
| sequence_len: 2048 |
| sample_packing: true |
| pad_to_sequence_len: true |
| |
| adapter: qlora |
| lora_model_dir: |
| lora_r: 64 |
| lora_alpha: 32 |
| lora_dropout: 0.05 |
| lora_target_linear: true |
| lora_fan_in_fan_out: |
| |
| wandb_project: |
| wandb_entity: |
| wandb_watch: |
| wandb_name: |
| wandb_log_model: |
| |
| gradient_accumulation_steps: 1 |
| micro_batch_size: 2 |
| num_epochs: 4 |
| optimizer: adamw_torch |
| adam_beta2: 0.95 |
| adam_epsilon: 0.00001 |
| max_grad_norm: 1.0 |
| lr_scheduler: cosine |
| learning_rate: 0.000003 |
| |
| train_on_inputs: false |
| group_by_length: false |
| bf16: auto |
| fp16: |
| tf32: true |
| |
| gradient_checkpointing: true |
| gradient_checkpointing_kwargs: |
| use_reentrant: True |
| early_stopping_patience: |
| resume_from_checkpoint: |
| local_rank: |
| logging_steps: 1 |
| xformers_attention: |
| flash_attention: true |
| |
| warmup_steps: 100 |
| evals_per_epoch: 4 |
| saves_per_epoch: 1 |
| debug: |
| deepspeed: |
| weight_decay: 0.1 |
| fsdp: |
| fsdp_config: |
| resize_token_embeddings_to_32x: true |
| special_tokens: |
| pad_token: "<|endoftext|>" |
| |
| ``` |
|
|
| </details><br> |
|
|
| # phi-sft-out |
|
|
| This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.2548 |
|
|
| ## 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: 3e-06 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 100 |
| - num_epochs: 4 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 1.0668 | 0.0 | 1 | 1.2826 | |
| | 0.9408 | 0.25 | 580 | 1.2613 | |
| | 1.2121 | 0.5 | 1160 | 1.2559 | |
| | 0.9644 | 0.75 | 1740 | 1.2562 | |
| | 0.9582 | 1.0 | 2320 | 1.2556 | |
| | 1.0009 | 1.23 | 2900 | 1.2559 | |
| | 0.7816 | 1.48 | 3480 | 1.2556 | |
| | 0.9843 | 1.73 | 4060 | 1.2552 | |
| | 0.8877 | 1.98 | 4640 | 1.2559 | |
| | 0.8498 | 2.21 | 5220 | 1.2554 | |
| | 0.9163 | 2.46 | 5800 | 1.2550 | |
| | 1.0539 | 2.71 | 6380 | 1.2545 | |
| | 0.9533 | 2.96 | 6960 | 1.2547 | |
| | 0.6969 | 3.19 | 7540 | 1.2547 | |
| | 0.6204 | 3.44 | 8120 | 1.2547 | |
| | 0.891 | 3.69 | 8700 | 1.2548 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.8.2 |
| - Transformers 4.38.0.dev0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.0 |
