metadata
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-14B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 7b47b128-d1e3-40c4-93dd-fcfece88c160
results: []
See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: Qwen/Qwen2.5-14B-Instruct
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 2faaa280684be4c0_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/2faaa280684be4c0_train_data.json
type:
field_input: song
field_instruction: artist
field_output: text
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: 4
eval_max_new_tokens: 128
eval_steps: 150
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
group_by_length: true
hub_model_id: nttx/7b47b128-d1e3-40c4-93dd-fcfece88c160
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: 128
lora_dropout: 0.3
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
0: 75GB
max_steps: 3000
micro_batch_size: 4
mlflow_experiment_name: /tmp/2faaa280684be4c0_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: 150
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: 35de617b-f853-4dd3-bd2a-8c2a53791a53
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 35de617b-f853-4dd3-bd2a-8c2a53791a53
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null
7b47b128-d1e3-40c4-93dd-fcfece88c160
This model is a fine-tuned version of Qwen/Qwen2.5-14B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8755
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 3000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0003 | 1 | 2.2741 |
| 1.9671 | 0.0440 | 150 | 1.9967 |
| 1.9987 | 0.0879 | 300 | 1.9891 |
| 1.9462 | 0.1319 | 450 | 1.9864 |
| 1.9484 | 0.1759 | 600 | 1.9794 |
| 1.9302 | 0.2199 | 750 | 1.9671 |
| 1.9155 | 0.2638 | 900 | 1.9604 |
| 1.9415 | 0.3078 | 1050 | 1.9499 |
| 1.9503 | 0.3518 | 1200 | 1.9351 |
| 1.9144 | 0.3957 | 1350 | 1.9282 |
| 1.9094 | 0.4397 | 1500 | 1.9173 |
| 1.8951 | 0.4837 | 1650 | 1.9070 |
| 1.9383 | 0.5277 | 1800 | 1.9004 |
| 1.8939 | 0.5716 | 1950 | 1.8924 |
| 1.8584 | 0.6156 | 2100 | 1.8878 |
| 1.9155 | 0.6596 | 2250 | 1.8829 |
| 1.8812 | 0.7036 | 2400 | 1.8793 |
| 1.8444 | 0.7475 | 2550 | 1.8771 |
| 1.8464 | 0.7915 | 2700 | 1.8758 |
| 1.8568 | 0.8355 | 2850 | 1.8753 |
| 1.8577 | 0.8794 | 3000 | 1.8755 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1