shuttleai/shuttle-3.5-ckpts
1836
<!-- 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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/> <details><summary>See axolotl config</summary>
axolotl version: 0.9.0
# Weights and Biases logging config
wandb_project: shuttle-3.5
wandb_name: "3.5"
# Model architecture config
base_model: Qwen/Qwen3-32B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
chat_template: chatml
# Hugging Face saving config
hub_model_id: shuttleai/shuttle-3.5-ckpts
hub_strategy: all_checkpoints
# Model checkpointing config
output_dir: ./lora-out
saves_per_epoch: 10
save_safetensors: true
save_total_limit: 5
# Mixed precision training config
bf16: true
fp16: false
tf32: false
# Model loading config
load_in_8bit: false
load_in_4bit: true
strict: false
# Sequence config
sequence_len: 16384
s2_attention: false
sample_packing: true
eval_sample_packing: true
pad_to_sequence_len: true
train_on_inputs: false
group_by_length: false
# QLoRA adapter config
adapter: qlora
lora_r: 64
lora_alpha: 64
lora_dropout: 0.05
peft_use_dora: false
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
# Dataset config
datasets:
- path: ./dataset
type: chat_template
val_set_size: 0.05
evals_per_epoch: 10
dataset_prepared_path: ./prepared-datasets
shuffle_merged_datasets: true
# Training hyperparameters
num_epochs: 1
gradient_accumulation_steps: 2
micro_batch_size: 2
eval_batch_size: 1
warmup_steps: 500
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 2e-4
loraplus_lr_ratio: 8
cosine_min_lr_ratio: 0.1
weight_decay: 0.1
max_grad_norm: 1
logging_steps: 1
# Model optimization
gradient_checkpointing: unsloth
xformers_attention: false
flash_attention: true
sdp_attention: false
unsloth_cross_entropy_loss: true
unsloth_lora_mlp: false
unsloth_lora_qkv: false
unsloth_lora_o: false
# Loss monitoring config
early_stopping_patience: false
loss_watchdog_threshold: 100.0
loss_watchdog_patience: 3
# Debug config
debug: false
seed: 42
deepspeed: deepspeed_configs/zero2.json</details><br>
shuttle-3.5-ckpts
This model is a fine-tuned version of Qwen/Qwen3-32B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9783
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: 0.0002
- trainbatchsize: 2
- evalbatchsize: 1
- seed: 42
- distributed_type: multi-GPU
- gradientaccumulationsteps: 2
- totaltrainbatch_size: 4
- optimizer: Use OptimizerNames.PAGEDADAMW8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lrschedulertype: cosine
- lrschedulerwarmup_steps: 500
- num_epochs: 1.0
Training results
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
