See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: unsloth/Qwen2-7B-Instruct
bf16: false
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 9c695de64acac09c_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/9c695de64acac09c_train_data.json
type:
field_input: input
field_instruction: instruct
field_output: output
format: '{instruction} {input}'
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: true
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
greater_is_better: false
group_by_length: false
hub_model_id: JoshMe1/e31e6b1c-9225-4fd5-9a6e-e3ffc8a90251
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 5.0e-06
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
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_grad_norm: 0.3
max_memory:
0: 130GB
max_steps: 487
metric_for_best_model: eval_loss
micro_batch_size: 2
mlflow_experiment_name: /tmp/9c695de64acac09c_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: true
trust_remote_code: true
use_ema: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 29100ea8-8f91-45bb-841b-4a7bf8ea8b43
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 29100ea8-8f91-45bb-841b-4a7bf8ea8b43
warmup_ratio: 0.03
weight_decay: 0.01
xformers_attention: null
e31e6b1c-9225-4fd5-9a6e-e3ffc8a90251
This model is a fine-tuned version of unsloth/Qwen2-7B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2730
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: 5e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_HF with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: reduce_lr_on_plateau
- lr_scheduler_warmup_steps: 14
- training_steps: 487
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.0004 | 1 | 2.4640 |
1.4646 | 0.0432 | 100 | 1.4392 |
1.3411 | 0.0864 | 200 | 1.3339 |
1.2704 | 0.1296 | 300 | 1.2954 |
1.281 | 0.1727 | 400 | 1.2730 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
- Downloads last month
- 9
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support
Model tree for JoshMe1/e31e6b1c-9225-4fd5-9a6e-e3ffc8a90251
Base model
unsloth/Qwen2-7B-Instruct