Downloads · 30 days
3
30% of all-time downloads
VERSIL91/f4e02f87-283f-4a93-b31d-dc93f7273bad
f4e02f87-283f-4a93-b31d-dc93f7273bad is a machine learning model from VERSIL91. 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
3
30% of all-time downloads
All-time downloads
10
Public
Repo size
839 MB
Likes
0
Public
Click a slice to open those files.
.pt420 MB · 40%
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
dataset_prepared_path: null
datasets:
- data_files:
- 8cb8080a5a9882ee_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/8cb8080a5a9882ee_train_data.json
type:
field_instruction: question_1
field_output: answer
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device: cuda
early_stopping_patience: 1
eval_max_new_tokens: 128
eval_steps: 5
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: null
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: 3
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_memory:
0: 78GiB
max_steps: 30
micro_batch_size: 2
mlflow_experiment_name: /tmp/8cb8080a5a9882ee_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 10
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: true
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: a3f59e59-22c2-4996-8a6f-3d7a307b3322
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: a3f59e59-22c2-4996-8a6f-3d7a307b3322
warmup_steps: 5
weight_decay: 0.01
xformers_attention: true
</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 | 0.0094 | 1 | 1.6007 |
| 6.5907 | 0.0468 | 5 | 1.5055 |
| 5.6667 | 0.0937 | 10 | 1.2397 |
| 4.578 | 0.1405 | 15 | 1.2032 |
| 4.4109 | 0.1874 | 20 | 1.1597 |
| 4.5692 | 0.2342 | 25 | 1.1441 |
| 4.3347 | 0.2810 | 30 | 1.1402 |