Transformer_MT

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

• Loss: 2.2471
• Bleu: 0.4736

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: 1e-05
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 2
• training_steps: 2000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu
No log	2.53	200	2.4508	0.1996
No log	5.06	400	2.3803	0.3002
2.49	7.59	600	2.3398	0.4351
2.49	10.13	800	2.3148	0.3753
2.3247	12.66	1000	2.2919	0.4252
2.3247	15.19	1200	2.2747	0.4268
2.3247	17.72	1400	2.2633	0.4506
2.2349	20.25	1600	2.2563	0.4861
2.2349	22.78	1800	2.2486	0.4783
2.1924	25.32	2000	2.2471	0.4736

Framework versions

• Transformers 4.39.1
• Pytorch 2.1.2+cu121
• Datasets 2.16.0
• Tokenizers 0.15.0