Request
Hi Maziyar,
I was wondering if you could make a new model. I was hoping that you could train the below model on the mentioned database:
Base Model to finetune: https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT
Dataset to be used for training: https://huggingface.co/datasets/Arist12/EABF-ShareGPT-Long-3.5k
Something like this (I couldn't make the ShareGPT dataset work yet, but it does seem to work with the Alpaca)
base_model: NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT
model_type: MixtralForCausalLM
tokenizer_type: LlamaTokenizer
trust_remote_code: true
load_in_4bit: true
strict: false
# datasets:
# - path: Arist12/EABF-ShareGPT-Long-3.5k
# type: sharegpt
# conversation: chatml
datasets:
- path: tatsu-lab/alpaca
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.1
output_dir: ./qlora-out
# save_safetensors: true
adapter: qlora
lora_model_dir:
sequence_len: 1025
sample_packing: true
pad_to_sequence_len: true
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
# - gate
- q_proj
# - k_proj
- v_proj
# - o_proj
# - w1
# - w2
# - w3
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 1
optimizer: adamw_bnb_8bit
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
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_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>"
Is it possible to train that model with either one of these datasets?
https://huggingface.co/datasets/LargeWorldModel/ultrachat_qa_mix_128K
Or
https://huggingface.co/datasets/cris177/Arguments
@MaziyarPanahi ,Thank you very much. I was hoping to fine-tune a model on a large context dataset, but as you mentioned, the ShareGPT dataset is not working yet. Is it possible to fine-tune on another dataset, such as the one available at this link: https://huggingface.co/datasets/HuggingFaceTB/cosmopedia/viewer/wikihow? The mentioned dataset includes several subsets, but I am specifically interested in using Wikiwow, which consists of 179K rows.
Is it possible to train that model with either one of these datasets?
https://huggingface.co/datasets/LargeWorldModel/ultrachat_qa_mix_128K
Or
https://huggingface.co/datasets/cris177/Arguments
Of course! I'll give it a shot and hopefully the datasets are straightforward in axolotl.
@MaziyarPanahi ,Thank you very much. I was hoping to fine-tune a model on a large context dataset, but as you mentioned, the ShareGPT dataset is not working yet. Is it possible to fine-tune on another dataset, such as the one available at this link: https://huggingface.co/datasets/HuggingFaceTB/cosmopedia/viewer/wikihow? The mentioned dataset includes several subsets, but I am specifically interested in using Wikiwow, which consists of 179K rows.
This looks nice, should be OK as far as I can see.
I fine-tuned it on a 53k Alpaca dataset just for a test, could you please let me know if it's working properly before we go forward with other datasets: https://huggingface.co/MaziyarPanahi/Nous-Hermes-2-Mixtral-8x7B-SFT-Alpaca
Thank you so much for your great job! I appreciate your efforts. I kindly request that you consider training the Nous-Hermes-2-Mixtral-8x7B-SFT model on this database as well: https://huggingface.co/datasets/HuggingFaceTB/cosmopedia/viewer/wikihow
Additionally, please create a GGUF version of the following model: https://huggingface.co/MaziyarPanahi/Nous-Hermes-2-Mixtral-8x7B-SFT-Alpaca
And if you're planning on creating future model by using wikihow dataset, I would be grateful if you could also create a GGUF version of that as well. Thank you for your time and efforts!