tatoeba-tok-en

This model is a fine-tuned version of Helsinki-NLP/opus-mt-ru-en on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.4103
• Bleu: 24.8720

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu
1.9475	1.0	1167	1.7238	18.0675
1.6448	2.0	2334	1.5780	20.8358
1.4672	3.0	3501	1.5123	22.5640
1.3647	4.0	4668	1.4765	23.4342
1.2831	5.0	5835	1.4523	24.3822
1.2213	6.0	7002	1.4393	24.6540
1.1609	7.0	8169	1.4295	25.0382
1.1231	8.0	9336	1.4235	24.8617
1.076	9.0	10503	1.4165	23.6289
1.0489	10.0	11670	1.4162	25.8471
1.0174	11.0	12837	1.4112	25.1640
0.9961	12.0	14004	1.4114	22.6132
0.9735	13.0	15171	1.4110	25.1948
0.9597	14.0	16338	1.4103	23.6949
0.9519	15.0	17505	1.4107	24.2304

Framework versions

• Transformers 4.52.4
• Pytorch 2.7.1+cu128
• Datasets 3.6.0
• Tokenizers 0.21.1