results2

This model is a fine-tuned version of dandelin/vilt-b32-mlm on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 54.5580
• Bleu Score: {'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 5.701223175160721e-08, 'length_ratio': 0.05656108597285068, 'translation_length': 300, 'reference_length': 5304}

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: 8
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu Score
620.8193	1.0	63	177.3467	{'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 5.701223175160721e-08, 'length_ratio': 0.05656108597285068, 'translation_length': 300, 'reference_length': 5304}
140.721	2.0	126	65.7476	{'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 5.701223175160721e-08, 'length_ratio': 0.05656108597285068, 'translation_length': 300, 'reference_length': 5304}
60.0697	3.0	189	54.5580	{'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 5.701223175160721e-08, 'length_ratio': 0.05656108597285068, 'translation_length': 300, 'reference_length': 5304}

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1