README.md

metadata

library_name: transformers
license: other
base_model: ByteDance-Seed/UI-TARS-1.5-7B
tags:
  - llama-factory
  - full
  - generated_from_trainer
model-index:
  - name: >-
      ui_tars_7b_easyr1_10k_hard_qwen7b_easy_gta1-4MP_lr_1_0e-06_bs_1_epochs_1.0_max_pixels_4000000_deepspeed
    results: []

ui_tars_7b_easyr1_10k_hard_qwen7b_easy_gta1-4MP_lr_1_0e-06_bs_1_epochs_1.0_max_pixels_4000000_deepspeed

This model is a fine-tuned version of ByteDance-Seed/UI-TARS-1.5-7B on the easyr1-10k-hard-qwen7b-easy-gta1-4MP dataset.

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-06
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• total_train_batch_size: 8
• total_eval_batch_size: 64
• 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: 0.1
• num_epochs: 1.0

Training results

Framework versions

• Transformers 4.52.4
• Pytorch 2.7.1+cu126
• Datasets 3.6.0
• Tokenizers 0.21.1