test_tambouille

This model is a fine-tuned version of vidore/colqwen2-base on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 1.0650
• eval_model_preparation_time: 0.0048
• eval_runtime: 25.2861
• eval_samples_per_second: 2.373
• eval_steps_per_second: 0.593
• step: 0

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: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 1

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.20.0