Modelpublic

Rodo-Sami/aaa80cff-d19f-4317-8f14-077ee22152d2

sourceHugging Facellama3.2updated 2y agoView on Hugging Face

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Model Card

<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/> <details><summary>See axolotl config</summary>

axolotl version: 0.5.2

yaml

adapter: lora
base_model: unsloth/Llama-3.2-1B-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 169b7f2c0d883c11_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/169b7f2c0d883c11_train_data.json
  type:
    field_input: keywords
    field_instruction: title
    field_output: presentation
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 1
eval_max_new_tokens: 128
eval_steps: 25
eval_table_size: null
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 16
gradient_checkpointing: true
group_by_length: true
hub_model_id: Rodo-Sami/aaa80cff-d19f-4317-8f14-077ee22152d2
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: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_steps: 100
micro_batch_size: 4
mlflow_experiment_name: /tmp/169b7f2c0d883c11_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
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
sequence_len: 2048
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: disabled
wandb_name: aaa80cff-d19f-4317-8f14-077ee22152d2
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: aaa80cff-d19f-4317-8f14-077ee22152d2
warmup_ratio: 0.05
weight_decay: 0.01
xformers_attention: true

</details><br>

aaa80cff-d19f-4317-8f14-077ee22152d2

This model is a fine-tuned version of unsloth/Llama-3.2-1B-Instruct on the None dataset. It achieves the following results on the evaluation set:

—Loss: 0.6466

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
—trainbatchsize: 4
—evalbatchsize: 4
—seed: 42
—distributed_type: multi-GPU
—num_devices: 4
—gradientaccumulationsteps: 16
—totaltrainbatch_size: 256
—totalevalbatch_size: 16
—optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
—lrschedulertype: cosine
—lrschedulerwarmup_steps: 4
—training_steps: 84

Training results

Training Loss	Epoch	Step	Validation Loss
4.3178	0.0239	1	4.4951
0.6539	0.5979	25	0.6680
0.637	1.2078	50	0.6513
0.6372	1.8057	75	0.6466

Framework versions

—PEFT 0.13.2
—Transformers 4.46.3
—Pytorch 2.3.1+cu121
—Datasets 3.1.0
—Tokenizers 0.20.3