metadata
base_model:
- meta-llama/Llama-3.2-3B-Instruct
library_name: transformers
tags:
- mergekit
- merge
license: llama3.2
datasets:
- Fischerboot/small-boi-thinkin
language:
- en
Llama-3.2-3B-SmartBoi
This is a finetune to include 'thinking' tags (plus others).
It makes this model a lot smarter (at least in maths), alltho the tags are only used in english somehow.
This model has not been made uncensored.
Prompt Template
This Model uses Llama-3 Chat:
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
This is text
{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
Finetune Info:
The following YAML configuration was used to finetune this model:
base_model: alpindale/Llama-3.2-3B-Instruct
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: true
strict: false
chat_template: llama3
datasets:
- path: Fischerboot/small-boi-thinkin
type: sharegpt
conversation: llama3
dataset_prepared_path: last_run_prepared
val_set_size: 0.1
output_dir: ./outputs/yuh
adapter: qlora
lora_model_dir:
sequence_len: 4096
sample_packing: false
pad_to_sequence_len: true
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
loss_watchdog_threshold: 8.0
loss_watchdog_patience: 3
eval_sample_packing: false
warmup_steps: 10
evals_per_epoch: 2
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 2
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
bos_token: "<|begin_of_text|>"
eos_token: "<|end_of_text|>"
pad_token: "<|end_of_text|>"
Training results:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5032 | 0.0000 | 1 | 1.6556 |
| 1.2011 | 0.5000 | 10553 | 0.6682 |