metadata
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-1.5B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: d1b8ff5d-b9aa-491a-baff-622a5ecd21bb
results: []
See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: Qwen/Qwen2.5-1.5B-Instruct
bf16: auto
bnb_config_kwargs:
bnb_4bit_quant_type: nf4
bnb_4bit_use_double_quant: true
chat_template: llama3
cosine_min_lr_ratio: 0.1
data_processes: 16
dataset_prepared_path: null
datasets:
- data_files:
- 422de410c10946dc_train_data.json
ds_type: json
path: /workspace/input_data/422de410c10946dc_train_data.json
type:
field_input: original-context
field_instruction: category
field_output: original-instruction
field_system: original-response
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device_map: '{'''':torch.cuda.current_device()}'
do_eval: true
early_stopping_patience: 1
eval_batch_size: 1
eval_sample_packing: false
eval_steps: 25
evaluation_strategy: steps
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 32
gradient_checkpointing: true
group_by_length: true
hub_model_id: cwaud/d1b8ff5d-b9aa-491a-baff-622a5ecd21bb
hub_repo: cwaud
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lora_target_modules:
- q_proj
- v_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
0: 70GiB
1: 70GiB
2: 70GiB
3: 70GiB
max_steps: 800
micro_batch_size: 1
mlflow_experiment_name: /tmp/422de410c10946dc_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 4
optim_args:
adam_beta1: 0.9
adam_beta2: 0.95
adam_epsilon: 1e-5
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: 50
save_strategy: steps
sequence_len: 2048
strict: false
tf32: false
tokenizer_type: AutoTokenizer
torch_compile: false
train_on_inputs: false
trust_remote_code: true
val_set_size: 50
wandb_entity: rayonlabs-rayon-labs
wandb_mode: online
wandb_name: d1b8ff5d-b9aa-491a-baff-622a5ecd21bb
wandb_project: Public_TuningSN
wandb_run: miner_id_24
wandb_runid: d1b8ff5d-b9aa-491a-baff-622a5ecd21bb
warmup_raio: 0.03
warmup_ratio: 0.05
weight_decay: 0.01
xformers_attention: null
d1b8ff5d-b9aa-491a-baff-622a5ecd21bb
This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1941
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 23
- training_steps: 465
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.8785 | 0.0086 | 1 | 5.1108 |
| 2.4538 | 0.2152 | 25 | 1.5650 |
| 1.7722 | 0.4305 | 50 | 1.3281 |
| 1.8408 | 0.6457 | 75 | 1.2648 |
| 1.6735 | 0.8609 | 100 | 1.2357 |
| 0.8049 | 1.0761 | 125 | 1.2327 |
| 0.8683 | 1.2914 | 150 | 1.2016 |
| 0.8795 | 1.5066 | 175 | 1.1929 |
| 0.797 | 1.7218 | 200 | 1.1888 |
| 0.8046 | 1.9370 | 225 | 1.1573 |
| 0.9134 | 2.1523 | 250 | 1.1941 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1