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empower-functions-more-tools
liuylhf/empower-functions-more-tools
empower-functions-more-tools 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 15, 2024
- Updated
- Mar 15, 2024
- SHA
- 3a633465
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
adapter: qlora
base_model: mistralai/Mixtral-8x7B-Instruct-v0.1
bf16: true
chat_template: inst
dataset_prepared_path: last_run_prepared
datasets:
- conversation: mistral
path: ./data/with_function_response/function_not_used_training_small.jsonl
type: sharegpt
- conversation: mistral
path: ./data/with_function_response/more_functions/function_used_training_small.jsonl
type: sharegpt
debug: null
eval_max_new_tokens: 256
eval_steps: 0.2
eval_table_size: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: liuylhf/empower-functions-more-tools
learning_rate: 0.0002
load_in_4bit: true
load_in_8bit: false
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.05
lora_model_dir: null
lora_r: 32
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
loss_watchdog_patience: 3
loss_watchdog_threshold: 5.0
lr_scheduler: cosine
micro_batch_size: 2
model_config:
output_router_logits: true
model_type: AutoModelForCausalLM
num_epochs: 2
optimizer: paged_adamw_8bit
output_dir: 2af0968cad514d6e9d5fb8448230e1c6/model
pad_to_sequence_len: true
sample_packing: true
save_steps: 0.1
sequence_len: 4096
strict: false
tf32: false
tokenizer_type: LlamaTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_log_model: end
wandb_name: mixtral-instruct-lora-no-negative
wandb_project: function-call
warmup_steps: 10
weight_decay: 0.0
empower-functions-more-tools
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: 0.0899
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
- 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=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.8129 | 0.0 | 1 | 2.0522 |
| 0.1202 | 0.4 | 104 | 0.1054 |
| 0.1092 | 0.8 | 208 | 0.0976 |
| 0.0861 | 1.18 | 312 | 0.0938 |
| 0.0689 | 1.58 | 416 | 0.0908 |
| 0.0865 | 1.98 | 520 | 0.0899 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0
- Library
- peft
- Type
- mixtral
- License
- apache-2.0
- Created
- Mar 15, 2024
- Updated
- Mar 15, 2024