See axolotl config
axolotl version: 0.9.0
## model
base_model: SillyTilly/ServiceNow-AI-Apriel-Nemotron-15b-Thinker-Chatml
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
## qlora COPE
load_in_8bit: false
load_in_4bit: false
strict: false
## data
datasets:
datasets:
- path: Delta-Vector/Ursa-Erebus-16K
type: completion
field: body
- path: Delta-Vector/Ursa-Books-Light-Novels-V1
type: completion
field: text
- path: NewEden/Orion-LIT
type: completion
field: text
- path: Delta-Vector/Ursa-Asstr-V2-18k
type: completion
field: content
- path: Delta-Vector/Ursa-Books-V2
type: completion
field: text
- path: Delta-Vector/Ursa-Scribblehub-7k
type: completion
field: text
# - path: Delta-Vector/Ursa-SCP-wiki-1.9K
# type: completion
# field: text
- path: Delta-Vector/Ursa-Orion-EA-Comp-Filtered
type: completion
field: Text
- path: Delta-Vector/Ursa-HoneyFeed
type: completion
field: text
- path: Delta-Vector/Ursa-Falling-through-the-world
type: completion
field: content
shuffle_merged_datasets: true
dataset_prepared_path: dataset_preparedss
val_set_size: 0.0
output_dir: ./Rae-15B-Pretrain
## Liger + CCE
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
liger_fused_linear_cross_entropy: false
cut_cross_entropy: true
## CTX settings
sequence_len: 16384
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
## max grad norm
max_grad_norm: 0.001
## WandB
wandb_project: Rae
wandb_entity:
wandb_watch:
wandb_name: Pretrain-15B
wandb_log_model:
## evals
#evals_per_epoch: 0
#eval_table_size:
#eval_max_new_tokens: 128
## hoe params
gradient_accumulation_steps: 2
micro_batch_size: 2
num_epochs: 1
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 1e-5
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
s2_attention:
warmup_steps: 50
saves_per_epoch: 2
debug:
deepspeed: ./deepspeed_configs/zero3_bf16.json
weight_decay: 0.0001
fsdp:
fsdp_config:
special_tokens:
pad_token: <pad>
Rae-15B-Pretrain
This model is a fine-tuned version of SillyTilly/ServiceNow-AI-Apriel-Nemotron-15b-Thinker-Chatml on the Delta-Vector/Ursa-Erebus-16K, the Delta-Vector/Ursa-Books-Light-Novels-V1, the NewEden/Orion-LIT, the Delta-Vector/Ursa-Asstr-V2-18k, the Delta-Vector/Ursa-Books-V2, the Delta-Vector/Ursa-Scribblehub-7k, the Delta-Vector/Ursa-Orion-EA-Comp-Filtered, the Delta-Vector/Ursa-HoneyFeed and the Delta-Vector/Ursa-Falling-through-the-world datasets.
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- total_eval_batch_size: 12
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- num_epochs: 1.0
Training results
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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