sleepdeprived3/Scifi-Roleplay-24B-v1.0-LoRA

See axolotl config

axolotl version: 0.8.1

base_model: TheDrummer/Cydonia-24B-v2.1
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

model_config:
  trust_remote_code: true
  tokenizer:
    pad_token: "</s>"
    padding_side: "right"
    add_bos_token: true
    add_eos_token: false

datasets:
  - path: data/data.jsonl
    type: chat_template
    chat_template_strategy: tokenizer
    field_messages: conversations
    message_property_mappings:
      role: role
      content: content
    roles:
      user: ["user"]
      assistant: ["assistant"]
      system: ["system"]

load_in_4bit: true
adapter: qlora
lora_r: 64
lora_alpha: 32
lora_dropout: 0.1
lora_target_modules:
  - q_proj
  - k_proj
  - v_proj
  - o_proj
  - gate_proj
  - up_proj
  - down_proj

bf16: true
flash_attention: true
gradient_checkpointing: true
deepspeed: deepspeed_configs/zero2.json

gradient_accumulation_steps: 4
micro_batch_size: 8
num_epochs: 3
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 3e-6
warmup_ratio: 0.02

max_seq_length: 8192
pad_to_sequence_len: true
sample_packing: true
max_grad_norm: 1.0

output_dir: ./output
save_steps: 100
logging_steps: 10
save_safetensors: true

special_tokens:
  pad_token: "</s>"

output

This model is a fine-tuned version of TheDrummer/Cydonia-24B-v2.1 on the data/data.jsonl 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: 3e-06
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• 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: 33
• num_epochs: 3.0

Training results

Framework versions

• PEFT 0.15.1
• Transformers 4.51.0
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1