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Model: justinj92/phi2-bunny Source: Original Platform
2026-05-05 10:42:37 +08:00
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+---
+license: mit
+library_name: transformers
+tags:
+- axolotl
+- generated_from_trainer
+base_model: microsoft/phi-2
+model-index:
+- name: phi2-bunny
+  results: []
+datasets:
+- WhiteRabbitNeo/WRN-Chapter-1
+- WhiteRabbitNeo/WRN-Chapter-2
+---
+
+<!-- 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-2
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+is_llama_derived_model: false
+# trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: WhiteRabbitNeo/WRN-Chapter-1
+    type:
+      system_prompt: ""
+      field_system: system
+      field_instruction: instruction
+      field_output: response
+    prompt_style: chatml
+  - path: WhiteRabbitNeo/WRN-Chapter-2
+    type:
+      system_prompt: ""
+      field_system: system
+      field_instruction: instruction
+      field_output: response
+    prompt_style: chatml
+
+dataset_prepared_path: ./phi2-bunny/last-run-prepared
+val_set_size: 0.05
+output_dir: ./phi2-bunny/
+
+sequence_len: 2048
+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:
+lora_modules_to_save:
+  - embed_tokens
+  - lm_head
+
+
+hub_model_id: justinj92/phi2-bunny
+
+wandb_project: phi2-bunny
+wandb_entity: justinjoy-5
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 8
+micro_batch_size: 2
+num_epochs: 5
+optimizer: paged_adamw_8bit
+adam_beta1: 0.9
+adam_beta2: 0.999
+adam_epsilon: 0.00001
+max_grad_norm: 1000.0
+lr_scheduler: cosine
+learning_rate: 0.0002
+
+train_on_inputs: false
+group_by_length: true
+bf16: true
+fp16: false
+tf32: true
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+auto_resume_from_checkpoints:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+chat_template: chatml
+
+warmup_steps: 100
+evals_per_epoch: 4
+save_steps: 0.01
+save_total_limit: 2
+debug:
+deepspeed:
+weight_decay: 0.01
+fsdp:
+fsdp_config:
+resize_token_embeddings_to_32x: true
+special_tokens:
+  eos_token: "<|im_end|>"
+  pad_token: "<|endoftext|>"
+tokens:
+  - "<|im_start|>"
+
+```
+
+</details><br>
+
+## Hardware
+
+Azure 1xNC_H100 VM - 8 Hours Training Time
+
+# phi2-bunny
+
+This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the WhiteRabbit Cybersecurity dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5347
+
+## Model description
+
+Phi-2 SLM
+
+## Intended uses & limitations
+
+Research & Learning
+
+## ChatML Prompt
+
+<|im_start|>system
+You are Bunny, a helpful AI cyber researcher. Answer the Question in a logical, step-by-step manner that makes the reasoning process clear. Carefully analyze the question to identify the core issue or problem to be solved.<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
+
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-05
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.8645        | 0.0   | 1    | 0.7932          |
+| 0.6246        | 0.25  | 228  | 0.6771          |
+| 0.6449        | 0.5   | 456  | 0.6186          |
+| 0.6658        | 0.75  | 684  | 0.6073          |
+| 0.5419        | 1.0   | 912  | 0.5911          |
+| 0.5477        | 1.24  | 1140 | 0.5878          |
+| 0.612         | 1.49  | 1368 | 0.5715          |
+| 0.6328        | 1.74  | 1596 | 0.5632          |
+| 0.5082        | 1.99  | 1824 | 0.5534          |
+| 0.5807        | 2.24  | 2052 | 0.5513          |
+| 0.4775        | 2.49  | 2280 | 0.5448          |
+| 0.514         | 2.74  | 2508 | 0.5430          |
+| 0.4943        | 2.99  | 2736 | 0.5398          |
+| 0.5012        | 3.22  | 2964 | 0.5396          |
+| 0.5203        | 3.48  | 3192 | 0.5371          |
+| 0.5112        | 3.73  | 3420 | 0.5356          |
+| 0.4978        | 3.98  | 3648 | 0.5351          |
+| 0.5642        | 4.22  | 3876 | 0.5348          |
+| 0.5383        | 4.47  | 4104 | 0.5348          |
+| 0.4679        | 4.72  | 4332 | 0.5347          |
+
+
+### Framework versions
+
+- PEFT 0.8.1.dev0
+- Transformers 4.37.0
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0