You can deploy this model and start earning money today!

haqishen/
v1_phi4_mini_bs1x2x2_lr1e4_dora64_128do80_4ep_final_lora

Name: v1_phi4_mini_bs1x2x2_lr1e4_dora64_128do80_4ep_final_lora
Availability: InStock

generated_from_trainer

microsoft/Phi-4-mini-instruct

adapter

other

Views

No views yet

v1_phi4_mini_bs1x2x2_lr1e4_dora64_128do80_4ep_final

This model is a fine-tuned version of microsoft/Phi-4-mini-instruct on the flock-task17-train and the flock-task17-valid datasets. It achieves the following results on the evaluation set:

Loss: 1.2161

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: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 2
total_train_batch_size: 4
total_eval_batch_size: 2
optimizer: Use paged_adamw_32bit 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: 20
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss
1.7604	0.3846	10	1.7769
1.6835	0.7692	20	1.5992
1.51	1.1538	30	1.4535
1.4703	1.5385	40	1.3788
1.4779	1.9231	50	1.3220
1.3191	2.3077	60	1.2911
1.263	2.6923	70	1.2614
1.3101	3.0769	80	1.2287
1.2759	3.4615	90	1.2190
1.1969	3.8462	100	1.2164

Framework versions

PEFT 0.15.1
Transformers 4.52.4
Pytorch 2.9.1+cu128
Datasets 3.5.0
Tokenizers 0.21.4

haqishen/v1_phi4_mini_bs1x2x2_lr1e4_dora64_128do80_4ep_final_lora

v1_phi4_mini_bs1x2x2_lr1e4_dora64_128do80_4ep_final

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

haqishen/
v1_phi4_mini_bs1x2x2_lr1e4_dora64_128do80_4ep_final_lora