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Alphatao/72cdbb0c-8d4b-4e9f-b8bc-add67049d21c
72cdbb0c-8d4b-4e9f-b8bc-add67049d21c 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.
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: The-matt/llama2_ko-7b_distinctive-snowflake-182_1060
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 6b153eae1acf64c1_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/6b153eae1acf64c1_train_data.json
type:
field_input: document_title
field_instruction: question
field_output: answer
format: '{instruction} {input}'
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/72cdbb0c-8d4b-4e9f-b8bc-add67049d21c
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: 1184
micro_batch_size: 4
mlflow_experiment_name: /tmp/6b153eae1acf64c1_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
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 5fbb6fa6-768c-4bc4-bac9-17a3ded9f842
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 5fbb6fa6-768c-4bc4-bac9-17a3ded9f842
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
</details><br>
This model is a fine-tuned version of The-matt/llama2_ko-7b_distinctive-snowflake-182_1060 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 |
|---|---|---|---|
| 2.3643 | 0.0012 | 1 | 2.6653 |
| 1.8862 | 0.1184 | 100 | 2.0343 |
| 1.7332 | 0.2367 | 200 | 1.9789 |
| 1.8496 | 0.3551 | 300 | 1.9495 |
| 1.9946 | 0.4734 | 400 | 1.9157 |
| 1.8303 | 0.5918 | 500 | 1.8862 |
| 1.9563 | 0.7102 | 600 | 1.8552 |
| 1.8997 | 0.8285 | 700 | 1.8299 |
| 1.6714 | 0.9469 | 800 | 1.8061 |
| 1.1119 | 1.0658 | 900 | 1.8516 |
| 1.2893 | 1.1842 | 1000 | 1.8479 |