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a411a2a2-036c-4b0f-9747-7c5e0c9b3409
vdos/a411a2a2-036c-4b0f-9747-7c5e0c9b3409
a411a2a2-036c-4b0f-9747-7c5e0c9b3409 is a machine learning model from vdos. 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. --
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At a glance
- Library
- peft
- License
- llama3.2
- Model type
- llama
- Access
- Public
- Created
- Dec 16, 2024
- Updated
- Dec 16, 2024
- SHA
- c6241000
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
<details><summary>See axolotl config</summary>
axolotl version: 0.5.2
adapter: lora
base_model: unsloth/Llama-3.2-3B
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 171a2b6e29515e8b_train_data.json
ds_type: json
field: text
path: /workspace/input_data/171a2b6e29515e8b_train_data.json
type: completion
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: vdos/a411a2a2-036c-4b0f-9747-7c5e0c9b3409
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: 50
micro_batch_size: 2
mlflow_experiment_name: /tmp/171a2b6e29515e8b_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
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: online
wandb_name: a411a2a2-036c-4b0f-9747-7c5e0c9b3409
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: a411a2a2-036c-4b0f-9747-7c5e0c9b3409
warmup_ratio: 0.05
weight_decay: 0.01
xformers_attention: true
a411a2a2-036c-4b0f-9747-7c5e0c9b3409
This model is a fine-tuned version of unsloth/Llama-3.2-3B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9397
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- 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: 2
- training_steps: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1076 | 0.0065 | 1 | 2.1259 |
| 1.7142 | 0.1616 | 25 | 1.9495 |
| 1.7106 | 0.3232 | 50 | 1.9397 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.3.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Library
- peft
- Type
- llama
- License
- llama3.2
- Created
- Dec 16, 2024
- Updated
- Dec 16, 2024