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Alphatao/
5e213a97-790e-495a-9451-77012edc2a8b

Name: 5e213a97-790e-495a-9451-77012edc2a8b
Availability: InStock

generated_from_trainer

Qwen/Qwen2.5-7B

adapter

apache-2.0

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: Qwen/Qwen2.5-7B
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - e1d136a86ab06d08_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/e1d136a86ab06d08_train_data.json
  type:
    field_input: input
    field_instruction: instruction
    field_output: responses
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/5e213a97-790e-495a-9451-77012edc2a8b
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
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
lora_target_modules:
- q_proj
- k_proj
- v_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 966
micro_batch_size: 4
mlflow_experiment_name: /tmp/e1d136a86ab06d08_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
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: 100
sequence_len: 1024
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.01843576242939103
wandb_entity: null
wandb_mode: online
wandb_name: c4fbd050-0dc5-4c85-b766-2c4450377849
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: c4fbd050-0dc5-4c85-b766-2c4450377849
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

5e213a97-790e-495a-9451-77012edc2a8b

This model is a fine-tuned version of Qwen/Qwen2.5-7B on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1216

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: 8
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_BNB 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: 966

Training results

Training Loss	Epoch	Step	Validation Loss
2.7473	0.0001	1	2.6677
0.1928	0.0120	100	0.1657
0.1531	0.0240	200	0.1583
0.1398	0.0361	300	0.1491
0.1442	0.0481	400	0.1428
0.1515	0.0601	500	0.1325
0.1609	0.0721	600	0.1290
0.1199	0.0841	700	0.1269
0.1683	0.0962	800	0.1233
0.0843	0.1082	900	0.1216

Framework versions

PEFT 0.13.2
Transformers 4.46.0
Pytorch 2.5.0+cu124
Datasets 3.0.1
Tokenizers 0.20.1