c6066e357bc49b7ad1217023e1f3b38c

This model is a fine-tuned version of google-t5/t5-3b on the Helsinki-NLP/opus_books [fi-no] dataset. It achieves the following results on the evaluation set:

• Loss: 2.0440
• Data Size: 1.0
• Epoch Runtime: 50.3120
• Bleu: 1.5657

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: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• total_train_batch_size: 32
• total_eval_batch_size: 32
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: constant
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Data Size	Epoch Runtime	Bleu
No log	0	0	3.6628	0	3.4841	0.1177
No log	1	85	3.3494	0.0078	4.7671	0.1216
No log	2	170	3.0615	0.0156	7.8142	0.1556
No log	3	255	2.8098	0.0312	12.5052	0.4017
No log	4	340	2.5535	0.0625	17.7541	0.4953
0.183	5	425	2.4453	0.125	25.5270	0.6522
0.183	6	510	2.3107	0.25	29.7544	0.7395
0.7676	7	595	2.1883	0.5	35.1289	0.9599
2.2418	8.0	680	2.0860	1.0	57.7765	1.0786
2.0376	9.0	765	2.0191	1.0	56.5626	1.1845
1.916	10.0	850	1.9799	1.0	48.8693	1.2901
1.8124	11.0	935	1.9564	1.0	49.6442	1.4012
1.6833	12.0	1020	1.9472	1.0	54.0012	1.4357
1.5883	13.0	1105	1.9318	1.0	47.0414	1.4677
1.4903	14.0	1190	1.9430	1.0	52.2791	1.5403
1.4006	15.0	1275	1.9667	1.0	48.3929	1.5809
1.3135	16.0	1360	2.0037	1.0	50.6084	1.5158
1.2223	17.0	1445	2.0440	1.0	50.3120	1.5657

Framework versions

• Transformers 4.57.0
• Pytorch 2.8.0+cu128
• Datasets 4.2.0
• Tokenizers 0.22.1