english-marathi-colloquial-translator

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

• Loss: 2.5470

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: 0.0003
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• 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
• lr_scheduler_warmup_steps: 2
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
3.2714	0.08	500	3.0344
3.4101	0.16	1000	2.9283
2.2733	0.24	1500	2.8800
1.8566	0.32	2000	2.8367
2.2548	0.4	2500	2.7989
3.447	0.48	3000	2.7752
2.304	0.56	3500	2.7567
3.1325	0.64	4000	2.7342
2.9546	0.72	4500	2.7158
2.9729	0.8	5000	2.7059
3.5754	0.88	5500	2.6906
3.8637	0.96	6000	2.6862
3.2746	1.04	6500	2.6655
2.9895	1.12	7000	2.6608
3.2698	1.2	7500	2.6436
2.1184	1.28	8000	2.6350
2.2134	1.3600	8500	2.6297
3.2429	1.44	9000	2.6204
2.8064	1.52	9500	2.6147
3.0127	1.6	10000	2.6057
3.2232	1.6800	10500	2.5991
2.2661	1.76	11000	2.5951
3.0668	1.8400	11500	2.5928
2.9571	1.92	12000	2.5847
3.2223	2.0	12500	2.5809
2.2106	2.08	13000	2.5771
3.1412	2.16	13500	2.5719
2.9079	2.24	14000	2.5671
2.5391	2.32	14500	2.5664
2.7341	2.4	15000	2.5613
3.0752	2.48	15500	2.5567
1.6035	2.56	16000	2.5563
2.6759	2.64	16500	2.5535
2.8205	2.7200	17000	2.5511
2.4317	2.8	17500	2.5474
2.816	2.88	18000	2.5473
3.0433	2.96	18500	2.5470

Framework versions

• PEFT 0.14.0
• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 3.3.1
• Tokenizers 0.21.0