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--- |
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license: mit |
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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: microsoft/Phi-3-mini-4k-instruct |
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model-index: |
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- name: isafpr-phi3-lora |
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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: `0.4.1` |
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```yaml |
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base_model: microsoft/Phi-3-mini-4k-instruct |
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trust_remote_code: true |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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chat_template: phi_3 |
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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: data/isaf_press_releases_ft.jsonl |
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conversation: alpaca |
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type: sharegpt |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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output_dir: ./outputs/phi3/lora-out |
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hub_model_id: strickvl/isafpr-phi3-lora |
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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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adapter: lora |
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lora_model_dir: |
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lora_r: 64 |
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lora_alpha: 32 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: isaf_pr_ft |
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wandb_entity: strickvl |
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gradient_accumulation_steps: 1 |
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micro_batch_size: 2 |
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num_epochs: 1 |
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optimizer: adamw_torch |
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adam_beta2: 0.95 |
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adam_epsilon: 0.00001 |
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max_grad_norm: 1.0 |
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lr_scheduler: cosine |
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learning_rate: 5.0e-6 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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gradient_checkpointing: true |
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gradient_checkpointing_kwargs: |
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use_reentrant: True |
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early_stopping_patience: 3 |
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logging_steps: 1 |
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flash_attention: true |
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eval_steps: 1000 |
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save_steps: 5000 |
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eval_table_size: 2 |
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eval_batch_size: 2 |
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eval_sample_packing: false |
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eval_max_new_tokens: 32 |
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eval_causal_lm_metrics: ["perplexity"] |
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do_causal_lm_eval: true |
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warmup_ratio: 0.2 |
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debug: true |
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weight_decay: 0.1 |
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resize_token_embeddings_to_32x: true |
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``` |
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</details><br> |
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# isafpr-phi3-lora |
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This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.2970 |
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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: 5e-06 |
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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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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 4 |
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- total_eval_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 53 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 7.0334 | 0.0038 | 1 | 3.2970 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
