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Alphatao/d22b4faa-1067-4d88-aec3-4361176df63a
d22b4faa-1067-4d88-aec3-4361176df63a is a machine learning model from Alphatao. 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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From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: princeton-nlp/Sheared-LLaMA-1.3B
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 2c346f6b850b5d7c_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/2c346f6b850b5d7c_train_data.json
type:
field_instruction: instruction
field_output: response
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
device_map:
? ''
: 0,1,2,3,4,5,6,7
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: true
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/d22b4faa-1067-4d88-aec3-4361176df63a
hub_repo: null
hub_strategy: null
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 2346
micro_batch_size: 4
mlflow_experiment_name: /tmp/2c346f6b850b5d7c_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
sequence_len: 2048
special_tokens:
pad_token: </s>
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.02513826043237808
wandb_entity: null
wandb_mode: online
wandb_name: 4c063dfa-dfa4-4dfa-b936-75e20c3b1a95
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 4c063dfa-dfa4-4dfa-b936-75e20c3b1a95
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
</details><br>
This model is a fine-tuned version of princeton-nlp/Sheared-LLaMA-1.3B on the None dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1364 | 0.0002 | 1 | 1.1052 |
| 0.8899 | 0.0165 | 100 | 0.9039 |
| 0.9399 | 0.0330 | 200 | 0.8800 |
| 0.7787 | 0.0495 | 300 | 0.8642 |
| 0.905 | 0.0660 | 400 | 0.8539 |
| 0.828 | 0.0825 | 500 | 0.8442 |
| 0.7606 | 0.0990 | 600 | 0.8366 |
| 0.8247 | 0.1155 | 700 | 0.8305 |
| 0.822 | 0.1320 | 800 | 0.8249 |
| 0.7917 | 0.1485 | 900 | 0.8190 |
| 0.8336 | 0.1650 | 1000 | 0.8137 |
| 0.793 | 0.1815 | 1100 | 0.8090 |
| 0.8341 | 0.1980 | 1200 | 0.8043 |
| 0.8041 | 0.2145 | 1300 | 0.8002 |
| 0.8371 | 0.2310 | 1400 | 0.7967 |
| 0.8139 | 0.2476 | 1500 | 0.7932 |
| 0.7202 | 0.2641 | 1600 | 0.7905 |
| 0.7889 | 0.2806 | 1700 | 0.7880 |
| 0.8812 | 0.2971 | 1800 | 0.7861 |
| 0.7821 | 0.3136 | 1900 | 0.7845 |
| 0.6997 | 0.3301 | 2000 | 0.7834 |
| 0.7337 | 0.3466 | 2100 | 0.7827 |
| 0.7729 | 0.3631 | 2200 | 0.7823 |
| 0.7764 | 0.3796 | 2300 | 0.7822 |