metadata
library_name: transformers
license: mit
base_model: ai4bharat/indictrans2-indic-indic-dist-320M
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: iitb_punct_orig_finetuned_eng_Ltn_to_mar_Deva
results: []
iitb_punct_orig_finetuned_eng_Ltn_to_mar_Deva
This model is a fine-tuned version of ai4bharat/indictrans2-indic-indic-dist-320M on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4013
- Bleu: 9.6977
- Gen Len: 20.8692
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 0.5705 | 0.3373 | 4000 | 0.5325 | 7.2659 | 20.7523 |
| 0.536 | 0.6746 | 8000 | 0.4951 | 7.9775 | 20.8722 |
| 0.4615 | 1.0119 | 12000 | 0.4757 | 8.1546 | 20.8717 |
| 0.4643 | 1.3492 | 16000 | 0.4606 | 8.4812 | 20.8716 |
| 0.4545 | 1.6865 | 20000 | 0.4496 | 8.6764 | 20.8743 |
| 0.4274 | 2.0238 | 24000 | 0.4421 | 8.7579 | 20.8725 |
| 0.4254 | 2.3611 | 28000 | 0.4341 | 8.937 | 20.8695 |
| 0.4089 | 2.6984 | 32000 | 0.4300 | 8.9973 | 20.8713 |
| 0.3813 | 3.0357 | 36000 | 0.4264 | 9.1282 | 20.8735 |
| 0.3794 | 3.3730 | 40000 | 0.4221 | 9.1568 | 20.8731 |
| 0.3887 | 3.7103 | 44000 | 0.4173 | 9.2067 | 20.8692 |
| 0.3416 | 4.0476 | 48000 | 0.4169 | 9.3934 | 20.8712 |
| 0.3581 | 4.3849 | 52000 | 0.4131 | 9.4104 | 20.8683 |
| 0.3596 | 4.7222 | 56000 | 0.4099 | 9.3756 | 20.8716 |
| 0.3244 | 5.0594 | 60000 | 0.4116 | 9.4521 | 20.872 |
| 0.3366 | 5.3967 | 64000 | 0.4085 | 9.4955 | 20.8652 |
| 0.3489 | 5.7340 | 68000 | 0.4056 | 9.4947 | 20.8741 |
| 0.3235 | 6.0713 | 72000 | 0.4075 | 9.4984 | 20.8682 |
| 0.3347 | 6.4086 | 76000 | 0.4054 | 9.5506 | 20.8708 |
| 0.328 | 6.7459 | 80000 | 0.4042 | 9.6531 | 20.8686 |
| 0.3169 | 7.0832 | 84000 | 0.4059 | 9.6254 | 20.8692 |
| 0.3137 | 7.4205 | 88000 | 0.4039 | 9.6441 | 20.8683 |
| 0.3063 | 7.7578 | 92000 | 0.4023 | 9.6607 | 20.8689 |
| 0.2955 | 8.0951 | 96000 | 0.4031 | 9.6606 | 20.8692 |
| 0.3082 | 8.4324 | 100000 | 0.4026 | 9.6643 | 20.8682 |
| 0.3133 | 8.7697 | 104000 | 0.4014 | 9.6642 | 20.8692 |
| 0.2981 | 9.1070 | 108000 | 0.4028 | 9.6811 | 20.8696 |
| 0.2857 | 9.4443 | 112000 | 0.4011 | 9.6914 | 20.8695 |
| 0.2868 | 9.7816 | 116000 | 0.4013 | 9.6977 | 20.8692 |
Framework versions
- Transformers 4.53.2
- Pytorch 2.9.0+cu128
- Datasets 2.21.0
- Tokenizers 0.21.4