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arcwarden46/dc74a896-5d2a-44ba-a0fa-18eebf093817
dc74a896-5d2a-44ba-a0fa-18eebf093817 is a machine learning model from arcwarden46. 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/zephyr-sft
bf16: true
chat_template: llama3
dataloader_num_workers: 24
dataset_prepared_path: null
datasets:
- data_files:
- 1b774a4dd8d7d670_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/1b774a4dd8d7d670_train_data.json
type:
field_instruction: instruction
field_output: output
format: '{instruction}'
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: 4
eval_max_new_tokens: 128
eval_steps: 400
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: true
hub_model_id: arcwarden46/dc74a896-5d2a-44ba-a0fa-18eebf093817
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: 40
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: 8000
micro_batch_size: 4
mlflow_experiment_name: /tmp/1b774a4dd8d7d670_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: 400
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: 3b9fa9f4-ca74-42a2-b0a4-b6d7627003c9
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 3b9fa9f4-ca74-42a2-b0a4-b6d7627003c9
warmup_steps: 40
weight_decay: 0.0
xformers_attention: null
</details><br>
This model is a fine-tuned version of unsloth/zephyr-sft 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 | 0.0002 | 1 | 1.9606 |
| 4.6356 | 0.0676 | 400 | 1.3429 |
| 4.6547 | 0.1352 | 800 | 1.2955 |
| 4.5705 | 0.2028 | 1200 | 1.2703 |
| 4.6352 | 0.2704 | 1600 | 1.2695 |
| 4.5863 | 0.3380 | 2000 | 1.2422 |
| 4.5649 | 0.4056 | 2400 | 1.2280 |
| 4.5416 | 0.4732 | 2800 | 1.2255 |
| 4.5812 | 0.5408 | 3200 | 1.1995 |
| 4.5234 | 0.6084 | 3600 | 1.1757 |
| 4.4131 | 0.6760 | 4000 | 1.1560 |
| 4.4123 | 0.7436 | 4400 | 1.1391 |
| 4.3572 | 0.8112 | 4800 | 1.1190 |
| 4.2639 | 0.8788 | 5200 | 1.1022 |
| 4.1995 | 0.9464 | 5600 | 1.0881 |
| 3.6816 | 1.0140 | 6000 | 1.0915 |
| 3.6266 | 1.0816 | 6400 | 1.0906 |
| 3.6469 | 1.1492 | 6800 | 1.0907 |