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Alphatao/b3e1f81d-8144-42a0-9bec-9e689ee71134
b3e1f81d-8144-42a0-9bec-9e689ee71134 is a machine learning model from Alphatao. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as llama3.2.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
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From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: unsloth/Llama-3.2-3B-Instruct
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- d0d5b03557816b62_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/d0d5b03557816b62_train_data.json
type:
field_input: rejected
field_instruction: task
field_output: chosen
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
device_map:
? ''
: 0,1,2,3,4,5,6,7
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: true
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/b3e1f81d-8144-42a0-9bec-9e689ee71134
hub_repo: null
hub_strategy: null
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: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 2017
micro_batch_size: 4
mlflow_experiment_name: /tmp/d0d5b03557816b62_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: 2048
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.02286006894596794
wandb_entity: null
wandb_mode: online
wandb_name: 8611164d-e487-4368-b17b-64865ae87740
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 8611164d-e487-4368-b17b-64865ae87740
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
</details><br>
This model is a fine-tuned version of unsloth/Llama-3.2-3B-Instruct on the None dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7961 | 0.0001 | 1 | 0.8303 |
| 0.6395 | 0.0150 | 100 | 0.6271 |
| 0.6059 | 0.0299 | 200 | 0.6157 |
| 0.5343 | 0.0449 | 300 | 0.6092 |
| 0.5676 | 0.0599 | 400 | 0.6029 |
| 0.6323 | 0.0749 | 500 | 0.5998 |
| 0.6282 | 0.0898 | 600 | 0.5949 |
| 0.6356 | 0.1048 | 700 | 0.5914 |
| 0.6045 | 0.1198 | 800 | 0.5875 |
| 0.5589 | 0.1348 | 900 | 0.5842 |
| 0.5782 | 0.1497 | 1000 | 0.5803 |
| 0.5731 | 0.1647 | 1100 | 0.5771 |
| 0.6077 | 0.1797 | 1200 | 0.5743 |
| 0.6219 | 0.1946 | 1300 | 0.5717 |
| 0.5129 | 0.2096 | 1400 | 0.5696 |
| 0.5544 | 0.2246 | 1500 | 0.5677 |
| 0.5021 | 0.2396 | 1600 | 0.5662 |
| 0.5141 | 0.2545 | 1700 | 0.5650 |
| 0.5114 | 0.2695 | 1800 | 0.5644 |
| 0.5372 | 0.2845 | 1900 | 0.5641 |
| 0.5472 | 0.2995 | 2000 | 0.5640 |