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Fischerboot/
adapter-goofy

Name: adapter-goofy
Availability: InStock

peft

HelpingAI

generated_from_trainer

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See axolotl config

axolotl version: 0.4.1

yaml

base_model: UnfilteredAI/NSFW-3B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: Fischerboot/freedom-rp-alpaca-shortend
    type: alpaca
  - path: Fischerboot/mongotom-40k-alpaca
    type: alpaca
  - path: TokenBender/roleplay_alpaca
    type: alpaca
    ds_type: parquet
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/32r

adapter: qlora
lora_model_dir:

sequence_len: 4096
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true

lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 2
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 0.0002

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

warmup_steps: 10
evals_per_epoch: 1
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
trust_remote_code: true

outputs/32r

This model is a fine-tuned version of UnfilteredAI/NSFW-3B on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.1202

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: 0.0002
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 10
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
8.0268	0.0032	1	3.2872
2.2591	1.0	314	2.1557
2.045	1.9753	628	2.1202

Framework versions

PEFT 0.11.1
Transformers 4.42.3
Pytorch 2.1.2+cu118
Datasets 2.19.1
Tokenizers 0.19.1

Fischerboot/adapter-goofy

outputs/32r

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Fischerboot/
adapter-goofy