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nttx/270a71ba-4f35-4d37-aeb6-9b40cda9d3ed
270a71ba-4f35-4d37-aeb6-9b40cda9d3ed is a machine learning model from nttx. 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. --
Downloads · 30 days
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.safetensors210 MB · 56%
From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: beomi/polyglot-ko-12.8b-safetensors
bf16: auto
chat_template: llama3
dataloader_num_workers: 24
dataset_prepared_path: null
datasets:
- data_files:
- 941bfdce941cd7f9_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/941bfdce941cd7f9_train_data.json
type:
field_input: Full-Document
field_instruction: Extract
field_output: Abstract
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device_map: auto
do_eval: true
early_stopping_patience: 2
eval_batch_size: 8
eval_max_new_tokens: 128
eval_steps: 250
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: true
hub_model_id: nttx/270a71ba-4f35-4d37-aeb6-9b40cda9d3ed
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 50
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
0: 75GB
max_steps: 1000
micro_batch_size: 8
mlflow_experiment_name: /tmp/941bfdce941cd7f9_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
optim_args:
adam_beta1: 0.9
adam_beta2: 0.95
adam_epsilon: 1e-5
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: 250
saves_per_epoch: null
sequence_len: 512
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: f23c7595-5a20-4117-93f6-e9e5a439dc97
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: f23c7595-5a20-4117-93f6-e9e5a439dc97
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null
</details><br>
This model is a fine-tuned version of beomi/polyglot-ko-12.8b-safetensors 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 |
|---|---|---|---|
| No log | 0.0001 | 1 | 2.3164 |
| 2.8883 | 0.0175 | 250 | 1.3935 |
| 2.7371 | 0.0350 | 500 | 1.3556 |
| 2.5963 | 0.0526 | 750 | 1.3090 |
| 2.5962 | 0.0701 | 1000 | 1.3020 |