This model is a fine-tuned version of Qwen/Qwen2.5-VL-7B-Instruct on the ui_tars_sft_data_8_frames_videos dataset. It achieves the following results on the evaluation set:

Loss: 0.0389

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: 1e-05
train_batch_size: 2
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 16
total_eval_batch_size: 8
optimizer: Use OptimizerNames.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: 6.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.0663	1.0	512	0.0679
0.029	2.0	1024	0.0360
0.0241	3.0	1536	0.0315
0.0094	4.0	2048	0.0305
0.0102	5.0	2560	0.0343
0.0039	6.0	3072	0.0389

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.0.2
Tokenizers 0.21.1

mlfoundations-cua-dev/ui-tars-1.5-7b-idm-full-sft-8-frames-videos

ui-tars-1.5-7b-idm-full-sft-8-frames-videos

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mlfoundations-cua-dev/
ui-tars-1.5-7b-idm-full-sft-8-frames-videos