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JoshMe1/d5930e8a-f1d1-42c2-8287-aeb43c727323
d5930e8a-f1d1-42c2-8287-aeb43c727323 is a machine learning model from JoshMe1. 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. --
Downloads · 30 days
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.pt1.3 GB · 40%
From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: lcw99/zephykor-ko-7b-chang
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 8abd12a03026eb74_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/8abd12a03026eb74_train_data.json
type:
field_instruction: text
field_output: completion_a
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device_map: auto
early_stopping_patience: 3
ema_decay: 0.9992
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
greater_is_better: false
group_by_length: false
hub_model_id: JoshMe1/d5930e8a-f1d1-42c2-8287-aeb43c727323
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: true
local_rank: null
logging_steps: 10
lora_alpha: 256
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: reduce_lr_on_plateau
lr_scheduler_factor: 0.5
lr_scheduler_patience: 2
max_memory:
0: 130GB
max_steps: 118
metric_for_best_model: eval_loss
micro_batch_size: 4
mlflow_experiment_name: /tmp/8abd12a03026eb74_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_hf
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
saves_per_epoch: null
sequence_len: 2048
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
use_ema: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 6fcc317d-215a-426f-8f02-24b244587de5
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 6fcc317d-215a-426f-8f02-24b244587de5
warmup_steps: 200
weight_decay: 0.01
xformers_attention: null
</details><br>
This model is a fine-tuned version of lcw99/zephykor-ko-7b-chang 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 | 0.0018 | 1 | 1.3587 |
| 4.389 | 0.1780 | 100 | 1.1028 |