finetune_colqwen2-v1.0

This model is a fine-tuned version of vidore/colqwen2-base on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.4260
• eval_model_preparation_time: 0.0093
• eval_runtime: 188.0038
• eval_samples_per_second: 0.532
• eval_steps_per_second: 0.266
• epoch: 0.4796
• step: 100

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: 3e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 1

Framework versions

• Transformers 4.46.3
• Pytorch 2.5.1+cu124
• Datasets 3.1.0
• Tokenizers 0.20.3