t5-base-finetuned-en-to-tr

This model is a fine-tuned version of t5-base on the setimes dataset. It achieves the following results on the evaluation set:

• Loss: 4.7522
• Bleu: 13.0464
• Gen Len: 17.5633

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
7.6012	1.0	12851	7.4685	2.2376	18.1521
7.0962	2.0	25702	6.8819	4.4861	18.0448
6.6712	3.0	38553	6.4648	6.1268	18.014
6.3473	4.0	51404	6.1421	7.6084	17.9027
6.1161	5.0	64255	5.8969	8.4021	17.7949
5.9178	6.0	77106	5.6935	9.37	17.8392
5.7331	7.0	89957	5.5226	9.8004	17.8893
5.5981	8.0	102808	5.3886	10.3562	17.8955
5.4867	9.0	115659	5.2807	10.876	17.7434
5.3722	10.0	128510	5.1751	11.1864	17.7313
5.2739	11.0	141361	5.0924	11.6223	17.6476
5.2339	12.0	154212	5.0033	11.8264	17.6996
5.1754	13.0	167063	4.9500	12.1915	17.6447
5.0981	14.0	179914	4.8958	12.4578	17.5782
5.0478	15.0	192765	4.8458	12.6398	17.5753
4.9778	16.0	205616	4.8142	12.6034	17.5681
4.9689	17.0	218467	4.7840	12.807	17.5816
4.9368	18.0	231318	4.7680	13.038	17.5614
4.9829	19.0	244169	4.7572	13.0403	17.5407
4.9434	20.0	257020	4.7522	13.0464	17.5633

Framework versions

• Transformers 4.34.1
• Pytorch 2.2.1+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1