This model is a fine-tuned version of microsoft/Phi-4-multimodal-instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 13.8976

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: 4e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.95) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
1.9923	0.2235	10	14.2728
0.3819	0.4469	20	14.0122
0.249	0.6704	30	14.0852
0.2951	0.8939	40	14.0115
0.2179	1.1117	50	14.0154
0.2839	1.3352	60	13.9879
0.2388	1.5587	70	14.0103
0.2687	1.7821	80	13.9336
0.1469	2.0	90	13.9879
0.1891	2.2235	100	13.9434
0.133	2.4469	110	14.0584
0.1759	2.6704	120	13.8902
0.1613	2.8939	130	13.8976

Framework versions

Transformers 4.51.3
Pytorch 2.4.1+cu124
Datasets 3.5.1
Tokenizers 0.21.1

TakalaWang/Discussion-Phi-4-multimodal-instruct

Discussion-Phi-4-multimodal-instruct-w-asr

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

TakalaWang/
Discussion-Phi-4-multimodal-instruct