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alchemist69/134522fa-81c7-4a65-8954-d27b0b7e0a89
134522fa-81c7-4a65-8954-d27b0b7e0a89 is a machine learning model from alchemist69. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: unsloth/Qwen2.5-1.5B
bf16: true
chat_template: llama3
dataloader_num_workers: 24
dataset_prepared_path: null
datasets:
- data_files:
- f5fa70a265d864c3_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/f5fa70a265d864c3_train_data.json
type:
field_input: constraint_type
field_instruction: constraint
field_output: ground_truth
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device_map: auto
do_eval: true
early_stopping_patience: 3
eval_batch_size: 2
eval_max_new_tokens: 128
eval_steps: 150
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: false
group_by_length: true
hub_model_id: alchemist69/134522fa-81c7-4a65-8954-d27b0b7e0a89
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 50
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_grad_norm: 1.0
max_steps: 3000
micro_batch_size: 2
mlflow_experiment_name: /tmp/f5fa70a265d864c3_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
optim_args:
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-8
optimizer: adamw_torch_fused
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 150
saves_per_epoch: null
sequence_len: 512
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 0462a67c-e855-4423-8ad5-29d7b2a5478e
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 0462a67c-e855-4423-8ad5-29d7b2a5478e
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null
</details><br>
This model is a fine-tuned version of unsloth/Qwen2.5-1.5B 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 |
|---|---|---|---|
| No log | 0.0011 | 1 | 2.4541 |
| 0.137 | 0.1704 | 150 | 0.1494 |
| 0.1144 | 0.3409 | 300 | 0.1069 |
| 0.1052 | 0.5113 | 450 | 0.1030 |
| 0.1002 | 0.6817 | 600 | 0.1007 |
| 0.0966 | 0.8522 | 750 | 0.0931 |
| 0.1165 | 1.0226 | 900 | 0.0891 |
| 0.0828 | 1.1930 | 1050 | 0.0872 |
| 0.0819 | 1.3634 | 1200 | 0.0851 |
| 0.0813 | 1.5339 | 1350 | 0.0855 |
| 0.0823 | 1.7043 | 1500 | 0.0848 |
| 0.0841 | 1.8747 | 1650 | 0.0844 |
| 0.0794 | 2.0452 | 1800 | 0.0849 |
| 0.078 | 2.2156 | 1950 | 0.0874 |
| 0.0686 | 2.3860 | 2100 | 0.0854 |