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---
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: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# iitb_punct_orig_finetuned_eng_Ltn_to_mar_Deva
This model is a fine-tuned version of [ai4bharat/indictrans2-indic-indic-dist-320M](https://huggingface.co/ai4bharat/indictrans2-indic-indic-dist-320M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4214
- Bleu: 9.1768
- Gen Len: 20.8676
## 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 |
|:-------------:|:------:|:------:|:---------------:|:------:|:-------:|
| 0.599 | 0.3373 | 4000 | 0.5677 | 6.4634 | 20.7483 |
| 0.5686 | 0.6746 | 8000 | 0.5257 | 7.1881 | 20.8685 |
| 0.495 | 1.0119 | 12000 | 0.5027 | 7.4899 | 20.8699 |
| 0.4929 | 1.3492 | 16000 | 0.4881 | 7.7787 | 20.8711 |
| 0.4806 | 1.6865 | 20000 | 0.4769 | 7.9328 | 20.8708 |
| 0.4517 | 2.0238 | 24000 | 0.4675 | 8.0617 | 20.8698 |
| 0.4536 | 2.3611 | 28000 | 0.4590 | 8.1686 | 20.8712 |
| 0.4355 | 2.6984 | 32000 | 0.4546 | 8.357 | 20.869 |
| 0.4036 | 3.0357 | 36000 | 0.4507 | 8.4307 | 20.8688 |
| 0.4021 | 3.3730 | 40000 | 0.4452 | 8.455 | 20.869 |
| 0.4097 | 3.7103 | 44000 | 0.4410 | 8.5307 | 20.8662 |
| 0.3623 | 4.0476 | 48000 | 0.4397 | 8.6425 | 20.8683 |
| 0.3823 | 4.3849 | 52000 | 0.4354 | 8.7187 | 20.8648 |
| 0.3822 | 4.7222 | 56000 | 0.4319 | 8.7131 | 20.8681 |
| 0.3434 | 5.0594 | 60000 | 0.4338 | 8.7598 | 20.869 |
| 0.3568 | 5.3967 | 64000 | 0.4296 | 8.8605 | 20.8626 |
| 0.3691 | 5.7340 | 68000 | 0.4272 | 8.8506 | 20.8722 |
| 0.3419 | 6.0713 | 72000 | 0.4295 | 8.9405 | 20.8697 |
| 0.3566 | 6.4086 | 76000 | 0.4262 | 9.0144 | 20.8692 |
| 0.3483 | 6.7459 | 80000 | 0.4258 | 9.0411 | 20.8695 |
| 0.3373 | 7.0832 | 84000 | 0.4259 | 9.0363 | 20.8659 |
| 0.3355 | 7.4205 | 88000 | 0.4252 | 9.0481 | 20.8665 |
| 0.3251 | 7.7578 | 92000 | 0.4227 | 9.0958 | 20.8655 |
| 0.3146 | 8.0951 | 96000 | 0.4234 | 9.0694 | 20.8682 |
| 0.3295 | 8.4324 | 100000 | 0.4226 | 9.1057 | 20.8662 |
| 0.3362 | 8.7697 | 104000 | 0.4219 | 9.1125 | 20.8652 |
| 0.3163 | 9.1070 | 108000 | 0.4229 | 9.1516 | 20.867 |
| 0.3061 | 9.4443 | 112000 | 0.4222 | 9.1548 | 20.8688 |
| 0.3074 | 9.7816 | 116000 | 0.4214 | 9.1768 | 20.8676 |
### Framework versions
- Transformers 4.53.2
- Pytorch 2.4.0a0+f70bd71a48.nv24.06
- Datasets 2.21.0
- Tokenizers 0.21.4
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