| | --- |
| | base_model: microsoft/Phi-3-mini-128k-instruct |
| | library_name: peft |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: out/yuh |
| | 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: `0.4.1` |
| | ```yaml |
| | base_model: microsoft/Phi-3-mini-128k-instruct |
| | trust_remote_code: true |
| | model_type: AutoModelForCausalLM |
| | tokenizer_type: AutoTokenizer |
| | chat_template: phi_3 |
| | |
| | load_in_8bit: false |
| | load_in_4bit: false |
| | strict: false |
| | |
| | datasets: |
| | - path: Fischerboot/freedom-rp-alpaca-shortend |
| | type: alpaca:phi |
| | - path: Fischerboot/mongotom-40k-alpaca |
| | type: alpaca:phi |
| | - path: Fischerboot/DAN-alpaca |
| | type: alpaca:phi |
| | |
| | dataset_prepared_path: |
| | val_set_size: 0.01 |
| | output_dir: ./out/yuh |
| | |
| | sequence_len: 1024 |
| | sample_packing: true |
| | pad_to_sequence_len: true |
| | |
| | adapter: lora |
| | lora_model_dir: |
| | lora_r: 64 |
| | lora_alpha: 32 |
| | lora_dropout: 0.05 |
| | lora_target_linear: true |
| | lora_fan_in_fan_out: |
| | |
| | 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: 5.0e-6 |
| | |
| | train_on_inputs: false |
| | group_by_length: false |
| | bf16: auto |
| | |
| | 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: 1 |
| | saves_per_epoch: 1 |
| | debug: |
| | deepspeed: |
| | weight_decay: 0.0 |
| | fsdp: |
| | fsdp_config: |
| | special_tokens: |
| | |
| | ``` |
| |
|
| | </details><br> |
| |
|
| | # out/yuh |
| |
|
| | This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 4.0955 |
| |
|
| | ## 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 |
| | - optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_steps: 10 |
| | - num_epochs: 4 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 4.296 | 0.0007 | 1 | 4.7549 | |
| | | 4.3774 | 1.0 | 1521 | 4.1032 | |
| | | 3.5409 | 1.9855 | 3042 | 4.0949 | |
| | | 3.8041 | 2.9711 | 4563 | 4.0953 | |
| | | 3.9558 | 3.9560 | 6084 | 4.0955 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.11.1 |
| | - Transformers 4.42.3 |
| | - Pytorch 2.1.2+cu118 |
| | - Datasets 2.19.1 |
| | - Tokenizers 0.19.1 |
