See axolotl config
axolotl version: 0.12.0.dev0
base_model: model
hub_model_id: hardlyworking/MS32-3
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true
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
load_in_8bit: false
load_in_4bit: true
chat_template: mistral_v7_tekken
datasets:
- path: PocketDoc/Dans-Prosemaxx-RepRemover-1
type: chat_template
split: train
field_messages: conversations
message_property_mappings:
role: from
content: value
user: human
assistant: gpt
- path: PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-2
type: chat_template
split: train
field_messages: conversations
message_property_mappings:
role: from
content: value
user: human
assistant: gpt
- path: Delta-Vector/Orion-Personamaxx-RP-Deslopped-V1
type: chat_template
split: train
field_messages: conversations
message_property_mappings:
role: from
content: value
user: human
assistant: gpt
- path: Delta-Vector/Orion-PIPPA-Cleaned-V2
type: chat_template
split: train
field_messages: conversations
message_property_mappings:
role: from
content: value
user: human
assistant: gpt
- path: Delta-Vector/Orion-Creative_Writing-Complexity
type: chat_template
split: train
field_messages: conversations
message_property_mappings:
role: from
content: value
user: human
assistant: gpt
- path: Delta-Vector/Orion-OpenCAI-ShareGPT
type: chat_template
split: train
field_messages: conversations
message_property_mappings:
role: from
content: value
user: human
assistant: gpt
- path: GreenerPastures/AllYourBase5k
type: chat_template
split: train
field_messages: conversations
message_property_mappings:
role: from
content: value
user: human
assistant: gpt
val_set_size: 0.0
output_dir: ./outputs/out
adapter: qlora
lora_r: 64
lora_alpha: 32
lora_dropout: 0.0
lora_target_linear: true
peft_use_rslora: true
sequence_len: 8192
sample_packing: true
eval_sample_packing: true
pad_to_sequence_len: true
wandb_project: MS32-3
wandb_entity:
wandb_watch:
wandb_name: MS32-3
wandb_log_model:
gradient_accumulation_steps: 32
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 4e-5
max_grad_norm: 1.0
bf16: auto
tf32: true
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
unsloth: true
resume_from_checkpoint:
logging_steps: 1
flash_attention: true
warmup_ratio: 0.1
evals_per_epoch:
saves_per_epoch: 4
weight_decay: 0.0025
special_tokens:
MS32-3
This model was trained from scratch on the PocketDoc/Dans-Prosemaxx-RepRemover-1, the PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-2, the Delta-Vector/Orion-Personamaxx-RP-Deslopped-V1, the Delta-Vector/Orion-PIPPA-Cleaned-V2, the Delta-Vector/Orion-Creative_Writing-Complexity, the Delta-Vector/Orion-OpenCAI-ShareGPT and the GreenerPastures/AllYourBase5k 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: 4e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_BNB 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: 10
- training_steps: 100
Training results
Framework versions
- PEFT 0.17.0
- Transformers 4.55.0
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
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