metadata
library_name: transformers
tags:
- generated_from_trainer
datasets:
- AlexHung29629/mbpii
model-index:
- name: outputs/gpt-oss-v2
results: []
See axolotl config
axolotl version: 0.13.0.dev0
base_model: ./gpt-oss-20b
use_kernels: false
model_quantization_config: Mxfp4Config
model_quantization_config_kwargs:
dequantize: true
plugins:
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
experimental_skip_move_to_device: true # prevent OOM by NOT putting model to GPU before sharding
unfrozen_parameters:
- \S+self_attn\S+
datasets:
- path: AlexHung29629/mbpii
type: chat_template
dataset_prepared_path: last_run_prepared
val_set_size: 0.05
output_dir: ./outputs/gpt-oss-v2
dataloader_num_workers: 0
dataloader_pin_memory: True
sequence_len: 16384
sample_packing: true
eval_sample_packing: false
remove_unused_columns: false
pad_to_sequence_len: true
wandb_project: mb_pii
wandb_name: v2
tensorboard: true
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_torch_fused
lr_scheduler: constant_with_warmup
learning_rate: 2e-6
save_only_model: true
tensorboard: true
bf16: true
tf32: true
#flash_attention: true
eager_attention: true
#sdp_attention: true
#attn_implementation: kernels-community/vllm-flash-attn3
#flex_attention: true
#flex_attn_compile_kwargs:
# dynamic: false
# mode: max-autotune-no-cudagraphs
torch_compile: true
#gradient_checkpointing: true
#activation_offloading: true
logging_steps: 1
saves_per_epoch: 1
warmup_ratio: 0.05
special_tokens:
eot_tokens:
- "<|end|>"
- "<|return|>"
fsdp_version: 2
fsdp_config:
offload_params: false
state_dict_type: FULL_STATE_DICT
auto_wrap_policy: TRANSFORMER_BASED_WRAP
transformer_layer_cls_to_wrap: GptOssDecoderLayer
reshard_after_forward: true
activation_checkpointing: true
outputs/gpt-oss-v2
This model was trained from scratch on the AlexHung29629/mbpii dataset.
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: 2e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- training_steps: 17
Training results
Framework versions
- Transformers 4.55.0
- Pytorch 2.7.1+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4