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mrcuddle
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tiny-darkllama-dpo

Text Generation
Transformers
PyTorch
Safetensors
llama
Generated from Trainer
conversational
text-generation-inference
Inference Endpoints
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tiny-darkllama-dpo / README.md
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metadata
library_name: transformers
license: other
base_model: mrcuddle/tiny-darkllama
tags:
  - generated_from_trainer
datasets:
  - Nitral-AI/Reddit-NSFW-Writing_Prompts_ShareGPT
model-index:
  - name: model-out
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.6.0

base_model: mrcuddle/tiny-darkllama
bf16: auto
datasets:
- chat_template: tokenizer_default
  field_messages: conversations
  message_field_content: value
  message_field_role: from
  path: Nitral-AI/Reddit-NSFW-Writing_Prompts_ShareGPT
  split: train
  type: chat_template
debug: null
deepspeed: null
early_stopping_patience: null
eval_sample_packing: true
eval_table_size: null
evals_per_epoch: 1
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: false
learning_rate: 2e-5
load_in_4bit: false
load_in_8bit: false
logging_steps: 1
lr_scheduler: cosine
max_steps: 25
micro_batch_size: 1
num_epochs: 1
optimizer: paged_adamw_8bit
pad_to_sequence_len: true
resume_from_checkpoint: null
sample_packing: true
saves_per_epoch: 1
sdp_attention: true
sequence_len: 2048
special_tokens:
  pad_token: <|end_of_text|>
strict: false
tf32: false
train_on_inputs: false
warmup_steps: 1
weight_decay: 0.0
xformers_attention: null

model-out

This model is a fine-tuned version of mrcuddle/tiny-darkllama on the Nitral-AI/Reddit-NSFW-Writing_Prompts_ShareGPT 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-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4
  • total_eval_batch_size: 2
  • optimizer: Use OptimizerNames.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: 2
  • training_steps: 25

Training results

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.21.0