metadata
library_name: transformers
tags:
- generated_from_trainer
datasets:
- AlexHung29629/train_0415_input_output
model-index:
- name: placeholder_sft/
results: []
See axolotl config
axolotl version: 0.8.1
base_model: ./placeholder_embed/merged/
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_glu_activation: true
liger_fused_linear_cross_entropy: true
datasets:
- path: AlexHung29629/train_0415_input_output
type: input_output
dataset_prepared_path: ./sft_dataprep/
val_set_size: 0
output_dir: ./placeholder_sft/
shuffle_merged_datasets: false
#eval_steps: 10
#eval_strategy:
sequence_len: 32768
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
wandb_project: Reasoning_TP1_2025
wandb_entity:
wandb_watch:
wandb_name: Mistral-24B-SFT-Reasoning-250414_sft
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 1
num_epochs: 5
optimizer: adamw_torch_fused
lr_scheduler: cosine
learning_rate: 1e-5
max_grad_norm: 1.0
adam_beta1: 0.9
adam_beta2: 0.95
adam_epsilon: 1e-8
bf16: true
tf32: false
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: true
logging_steps: 1
flash_attention: true
xformers_attention: false
sdp_attention: false
warmup_ratio: 0.05
saves_per_epoch: 1
save_total_limit: 5
weight_decay: 0.1
deepspeed: /mnt/shared/twsc/alex/reasoning/zero3_bf16.json
special_tokens:
pad_token: "<pad>"
#added_tokens_overrides: # Dict[int, str]
# 20: "<think>"
# 21: "</think>"
seed: 42
placeholder_sft/
This model was trained from scratch on the AlexHung29629/train_0415_input_output 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 64
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 246
- num_epochs: 5.0
Training results
Framework versions
- Transformers 4.51.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1