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Model: justinj92/phi2-bunny
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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

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special_tokens_map.json Normal file
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