metadata
library_name: peft
license: apache-2.0
base_model: unsloth/Qwen2.5-Math-1.5B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 51884d14-e23e-4b99-93e5-6ae20f825089
results: []
See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: unsloth/Qwen2.5-Math-1.5B-Instruct
bf16: true
chat_template: llama3
datasets:
- data_files:
- e1393a9aa0f354b5_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/e1393a9aa0f354b5_train_data.json
type:
field_instruction: title
field_output: context
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: false
hub_model_id: lesso04/51884d14-e23e-4b99-93e5-6ae20f825089
hub_repo: null
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: 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: 77GiB
max_steps: 50
micro_batch_size: 8
mlflow_experiment_name: /tmp/e1393a9aa0f354b5_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
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: 25
save_strategy: steps
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: 133fd195-f9a4-4ba8-b5e3-9e5b500eb2a8
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 133fd195-f9a4-4ba8-b5e3-9e5b500eb2a8
warmup_steps: 10
weight_decay: 0.01
xformers_attention: false
51884d14-e23e-4b99-93e5-6ae20f825089
This model is a fine-tuned version of unsloth/Qwen2.5-Math-1.5B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: nan
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- training_steps: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0 | 0.0001 | 1 | nan |
| 0.0 | 0.0004 | 5 | nan |
| 0.0 | 0.0007 | 10 | nan |
| 0.0 | 0.0011 | 15 | nan |
| 0.0 | 0.0014 | 20 | nan |
| 0.0 | 0.0018 | 25 | nan |
| 0.0 | 0.0021 | 30 | nan |
| 0.0 | 0.0025 | 35 | nan |
| 0.0 | 0.0028 | 40 | nan |
| 0.0 | 0.0032 | 45 | nan |
| 0.0 | 0.0035 | 50 | nan |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1