--- tags: - generated_from_trainer metrics: - bleu model-index: - name: English2AkuapemTwi results: [] --- # English2AkuapemTwi This model is a fine-tuned version of [allenai/unifiedqa-t5-small](https://huggingface.co/allenai/unifiedqa-t5-small) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.3098 - Bleu: 8.8875 - Gen Len: 17.5114 ## 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: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 30 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:| | 2.8304 | 1.0 | 2542 | 2.5363 | 0.2404 | 18.9072 | | 2.5079 | 2.0 | 5084 | 2.2533 | 0.5763 | 18.6814 | | 2.3362 | 3.0 | 7626 | 2.0838 | 0.8836 | 18.4972 | | 2.2155 | 4.0 | 10168 | 1.9649 | 1.3748 | 18.2368 | | 2.1066 | 5.0 | 12710 | 1.8767 | 2.0954 | 18.0588 | | 2.0368 | 6.0 | 15252 | 1.8057 | 2.6294 | 17.9451 | | 1.9641 | 7.0 | 17794 | 1.7436 | 3.0267 | 17.8342 | | 1.9194 | 8.0 | 20336 | 1.6907 | 3.4947 | 18.0199 | | 1.8474 | 9.0 | 22878 | 1.6438 | 4.0431 | 17.7758 | | 1.8261 | 10.0 | 25420 | 1.6008 | 4.4608 | 17.7919 | | 1.7833 | 11.0 | 27962 | 1.5642 | 4.9271 | 17.7868 | | 1.7255 | 12.0 | 30504 | 1.5322 | 5.3659 | 17.7962 | | 1.6913 | 13.0 | 33046 | 1.5020 | 5.9051 | 17.7301 | | 1.6616 | 14.0 | 35588 | 1.4780 | 6.0824 | 17.7217 | | 1.6522 | 15.0 | 38130 | 1.4550 | 6.6326 | 17.6227 | | 1.6039 | 16.0 | 40672 | 1.4327 | 6.7955 | 17.6564 | | 1.5926 | 17.0 | 43214 | 1.4119 | 7.0477 | 17.6876 | | 1.5802 | 18.0 | 45756 | 1.3960 | 7.4328 | 17.6233 | | 1.5438 | 19.0 | 48298 | 1.3816 | 7.4937 | 17.6359 | | 1.5452 | 20.0 | 50840 | 1.3695 | 7.7696 | 17.5515 | | 1.5423 | 21.0 | 53382 | 1.3569 | 7.9677 | 17.5596 | | 1.5076 | 22.0 | 55924 | 1.3465 | 8.2829 | 17.5193 | | 1.5183 | 23.0 | 58466 | 1.3386 | 8.4304 | 17.5486 | | 1.4919 | 24.0 | 61008 | 1.3296 | 8.536 | 17.5714 | | 1.4923 | 25.0 | 63550 | 1.3242 | 8.6446 | 17.4343 | | 1.488 | 26.0 | 66092 | 1.3177 | 8.7099 | 17.5126 | | 1.477 | 27.0 | 68634 | 1.3144 | 8.8431 | 17.5035 | | 1.4724 | 28.0 | 71176 | 1.3116 | 8.8588 | 17.5277 | | 1.4488 | 29.0 | 73718 | 1.3105 | 8.8989 | 17.5024 | | 1.4837 | 30.0 | 76260 | 1.3098 | 8.8875 | 17.5114 | ### Framework versions - Transformers 4.27.4 - Pytorch 2.0.0+cu118 - Datasets 2.11.0 - Tokenizers 0.13.3