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nttx/b68b8a84-63b9-49a6-94ce-c92b2c5ad284
b68b8a84-63b9-49a6-94ce-c92b2c5ad284 is a machine learning model from nttx. 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: dltjdgh0928/test_instruction
bf16: true
chat_template: llama3
dataloader_num_workers: 24
dataset_prepared_path: null
datasets:
- data_files:
- eb9250d3d2616e69_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/eb9250d3d2616e69_train_data.json
type:
field_input: keywords
field_instruction: captions_background
field_output: intention
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: 500
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: nttx/b68b8a84-63b9-49a6-94ce-c92b2c5ad284
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: 5000
micro_batch_size: 2
mlflow_experiment_name: /tmp/eb9250d3d2616e69_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: 500
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: 4eabefbe-2458-46f4-a26f-2456638d7f39
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 4eabefbe-2458-46f4-a26f-2456638d7f39
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null
</details><br>
This model is a fine-tuned version of dltjdgh0928/test_instruction 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 | 0.0004 | 1 | 2.7054 |
| 6.7657 | 0.1809 | 500 | 1.7205 |
| 6.5749 | 0.3619 | 1000 | 1.7143 |
| 6.2674 | 0.5428 | 1500 | 1.6468 |
| 6.0226 | 0.7238 | 2000 | 1.5607 |
| 5.7876 | 0.9047 | 2500 | 1.4811 |
| 4.0223 | 1.0857 | 3000 | 1.4806 |
| 3.9904 | 1.2666 | 3500 | 1.4531 |
| 3.847 | 1.4476 | 4000 | 1.4288 |
| 3.8327 | 1.6285 | 4500 | 1.4105 |
| 3.6422 | 1.8095 | 5000 | 1.4128 |