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Undi95/
toxicqa-Llama2-13B-lora

Name: toxicqa-Llama2-13B-lora
Availability: InStock

peft

safetensors

llama

generated_from_trainer

NousResearch/Llama-2-13b-hf

adapter

8-bit

bitsandbytes

Views

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Disclaimer: Toxic Content

This LoRA is based on a toxic dataset, and its responses when merged to a model may include content that is shocking or disturbing. It is essential to exercise caution and use the LoRA moderately, considering that the generated content is algorithmically derived from the training data. This LoRA is intended for uncensoring purposes only, and users assume responsibility for the interpretation and application of its outputs. I explicitly disclaim endorsement of any specific viewpoints represented in the training data. Additionally, it is crucial to note that the LoRA should not be used for any illegal activities. Users are hereby informed that I am not responsible for any misuse or negative consequences arising from the LoRA's use. Usage of this LoRA implies agreement with these terms.

See axolotl config

axolotl version: 0.3.0

yaml

base_model: NousResearch/Llama-2-13b-hf
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
is_llama_derived_model: true

load_in_8bit: true
load_in_4bit: false
strict: false

datasets:
  - path: dataset
    type: sharegpt
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./lora-out

sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true

adapter: lora
lora_model_dir:
lora_r: 128
lora_alpha: 64
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project: toxicLlama-2-13B
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 1
micro_batch_size: 2
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
eval_batch_size: 2

train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
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: 4
eval_table_size:
eval_table_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"

NobodyExistsOnTheInternet/ToxicQAtextFiltered

This model is a fine-tuned version of NousResearch/Llama-2-13b-hf on the NobodyExistsOnTheInternet/ToxicQAtextFiltered dataset. It achieves the following results on the evaluation set:

Loss: 0.7634

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0002
train_batch_size: 2
eval_batch_size: 2
seed: 42
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
1.0107	0.0	1	1.0286
0.8198	0.25	152	0.8079
0.7993	0.5	304	0.7904
0.7348	0.75	456	0.7748
0.689	1.0	608	0.7638
0.6462	1.23	760	0.7729
0.6226	1.48	912	0.7657
0.6179	1.73	1064	0.7634

Framework versions

Transformers 4.36.2
Pytorch 2.0.1+cu118
Datasets 2.16.1
Tokenizers 0.15.0

Training procedure

The following bitsandbytes quantization config was used during training:

quant_method: bitsandbytes
load_in_8bit: True
load_in_4bit: False
llm_int8_threshold: 6.0
llm_int8_skip_modules: None
llm_int8_enable_fp32_cpu_offload: False
llm_int8_has_fp16_weight: False
bnb_4bit_quant_type: fp4
bnb_4bit_use_double_quant: False
bnb_4bit_compute_dtype: float32

Framework versions

PEFT 0.6.0

Undi95/toxicqa-Llama2-13B-lora

Disclaimer: Toxic Content

NobodyExistsOnTheInternet/ToxicQAtextFiltered

Training hyperparameters

Training results

Framework versions

Training procedure

Framework versions

Undi95/
toxicqa-Llama2-13B-lora