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prxy5606/249c0f7b-0042-4300-ad8d-147d03f0ea64
249c0f7b-0042-4300-ad8d-147d03f0ea64 is a machine learning model from prxy5606. 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/Mistral-Nemo-Base-2407
bf16: true
chat_template: llama3
data_processes: 16
dataset_prepared_path: null
datasets:
- data_files:
- b2459ab0a181f103_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/b2459ab0a181f103_train_data.json
type:
field_instruction: role
field_output: text
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device_map: auto
do_eval: true
early_stopping_patience: 5
eval_batch_size: 2
eval_max_new_tokens: 128
eval_steps: 50
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: prxy5606/249c0f7b-0042-4300-ad8d-147d03f0ea64
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: 128
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
0: 75GB
max_steps: 200
micro_batch_size: 8
mlflow_experiment_name: /tmp/b2459ab0a181f103_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optim_args:
adam_beta1: 0.9
adam_beta2: 0.95
adam_epsilon: 1e-5
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: 50
saves_per_epoch: null
sequence_len: 1024
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: 27a8d31b-3d20-4d36-af74-7b08cf3c2129
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 27a8d31b-3d20-4d36-af74-7b08cf3c2129
warmup_steps: 20
weight_decay: 0.0
xformers_attention: null
</details><br>
This model is a fine-tuned version of unsloth/Mistral-Nemo-Base-2407 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 |
|---|---|---|---|
| 4.3506 | 0.0004 | 1 | 2.9484 |
| 19.0163 | 0.0190 | 50 | 2.4167 |
| 16.7287 | 0.0380 | 100 | 2.3730 |
| 16.1074 | 0.0570 | 150 | 2.2271 |
| 22.3368 | 0.0760 | 200 | 2.1559 |