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jerseyjerry/
task-5-microsoft-Phi-3-mini-4k-instruct-20250222

Name: task-5-microsoft-Phi-3-mini-4k-instruct-20250222
Availability: InStock

generated_from_trainer

microsoft/Phi-3-mini-4k-instruct

adapter

other

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lora

This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on the flock_task5_tranning dataset. It achieves the following results on the evaluation set:

Loss: 1.3370

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: 5e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 4
total_train_batch_size: 8
total_eval_batch_size: 2
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.05
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss
1.6968	0.4255	5	1.6353
1.4036	0.8511	10	1.5311
1.5081	1.3404	15	1.4970
1.4796	1.7660	20	1.4684
1.5587	2.2553	25	1.4455
1.2971	2.6809	30	1.4280
1.465	3.1702	35	1.4097
1.3267	3.5957	40	1.3954
1.3003	4.0851	45	1.3800
1.1868	4.5106	50	1.3672
1.3354	4.9362	55	1.3562
1.1273	5.4255	60	1.3492
1.2471	5.8511	65	1.3439
1.1704	6.3404	70	1.3409
1.1422	6.7660	75	1.3381
1.2064	7.2553	80	1.3379
1.2972	7.6809	85	1.3370

Framework versions

PEFT 0.12.0
Transformers 4.48.3
Pytorch 2.6.0+cu124
Datasets 3.2.0
Tokenizers 0.21.0

jerseyjerry/task-5-microsoft-Phi-3-mini-4k-instruct-20250222

lora

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jerseyjerry/
task-5-microsoft-Phi-3-mini-4k-instruct-20250222