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mixtral-lora-follow-instruction
liuylhf/mixtral-lora-follow-instruction
mixtral-lora-follow-instruction is a machine learning model from liuylhf. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Model type
- mixtral
- Access
- Public
- Created
- Mar 2, 2024
- Updated
- Mar 2, 2024
- SHA
- ae9d8f01
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
<details><summary>See axolotl config</summary>
axolotl version: 0.4.0
base_model: mistralai/Mixtral-8x7B-Instruct-v0.1
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
is_mistral_derived_model: true
load_in_8bit: false
load_in_4bit: true
strict: false
chat_template: inst
datasets:
- path: ./data/raw_format/tool_used_training_small.jsonl
type: sharegpt
conversation: mistral
- path: ./data/raw_format/tool_not_used_training_small.jsonl
type: sharegpt
conversation: mistral
- path: ./data/raw_format/no_tools_training_small.jsonl
type: sharegpt
conversation: mistral
- path: ./data/akoksal_lon_form.jsonl
type: sharegpt
conversation: mistral
- path: ./data/dolly.jsonl
type: sharegpt
conversation: mistral
dataset_prepared_path: last_run_prepared
val_set_size: 0.01
output_dir: ./mixtral-lora-2-epochs-r64
adapter: qlora
lora_model_dir:
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out:
hub_model_id: liuylhf/mixtral-lora-follow-instruction
hub_strategy: end
# lora_target_linear: true
model_config:
output_router_logits: true
lora_target_modules:
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project: function-call
wandb_name: mixtral-instruct-raw-data-v3
wandb_log_model: end
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 0.5
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 0.001
adam_beta2: 0.95
adam_epsilon: 0.00001
max_grad_norm: 1.0
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: 20
eval_steps: 0.5
save_steps: 0.5
eval_table_size:
eval_max_new_tokens: 256
# saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0
mixtral-lora-follow-instruction
This model is a fine-tuned version of mistralai/Mixtral-8x7B-Instruct-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6506
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: 0.001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 0.5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.0028 | 0.01 | 1 | 4.1157 |
| 0.6411 | 0.25 | 39 | 0.6506 |
Framework versions
- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.0
- Library
- peft
- Type
- mixtral
- License
- apache-2.0
- Created
- Mar 2, 2024
- Updated
- Mar 2, 2024