t5-small-finetuned-hausa-to-chinese

This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3817
• Bleu: 30.2633
• Gen Len: 3.5559

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: 0.0008
• train_batch_size: 32
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 4000
• num_epochs: 20
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
0.6981	1.0	846	0.2900	14.2476	3.4917
0.3149	2.0	1692	0.2639	18.6104	3.4725
0.2782	3.0	2538	0.2467	9.1092	3.2542
0.2622	4.0	3384	0.2481	24.1345	3.4047
0.2428	5.0	4230	0.2529	16.9217	3.3965
0.2271	6.0	5076	0.2491	27.8491	3.5349
0.2047	7.0	5922	0.2507	16.6565	3.339
0.1902	8.0	6768	0.2506	25.6462	3.5667
0.1739	9.0	7614	0.2610	27.1673	3.5916
0.1587	10.0	8460	0.2438	29.306	3.5839
0.1425	11.0	9306	0.2660	29.08	3.6478
0.1251	12.0	10152	0.2721	29.9148	3.4994
0.1105	13.0	10998	0.2929	28.1895	3.5526
0.0956	14.0	11844	0.3010	30.552	3.5717
0.083	15.0	12690	0.3307	27.9728	3.5303
0.0724	16.0	13536	0.3404	27.1874	3.5146
0.0652	17.0	14382	0.3592	29.9567	3.5529
0.0568	18.0	15228	0.3774	30.5145	3.5668
0.0549	19.0	16074	0.3795	30.6604	3.5637
0.0526	20.0	16920	0.3817	30.2633	3.5559

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1