Rotary IndicTrans2 Marathi to English Fine-Tune
Fine-tuned from prajdabre/rotary-indictrans2-indic-en-dist-200M on CIDCO train/val/test + all_documents_translated_progress_1.csv.
Training mode: LoRA (lr=5e-05).
Load
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
repo = "anuj1541/rotary-indictrans2-indic-en-mr-docs"
tokenizer = AutoTokenizer.from_pretrained(repo, trust_remote_code=True)
model = AutoModelForSeq2SeqLM.from_pretrained(repo, trust_remote_code=True)
Training
- Direction:
mar_Deva->eng_Latn - Epochs: 5
- Train pairs: 4,773
- Val pairs: 596
- Effective batch: 32
- LR: 5e-05
- Wall-clock: 2:15:40 (2.26 h)
- Finished: 2026-09-09T22:37:42
Packaged files
pytorch_model.bin, config.json, generation_config.json, tokenization_indictrans.py, tokenizer_config.json, dict.SRC.json, dict.TGT.json, model.SRC, model.TGT, configuration_rotary_indictrans.py, modeling_rotary_indictrans.py
Eval (500 samples, MR→EN, seed=42)
| Model | BLEU | ChrF | METEOR | TER | COMET | BERTF1 | Judge/5 |
|---|---|---|---|---|---|---|---|
rotary-base (prajdabre/rotary-indictrans2-indic-en-dist-200M) | 39.47 | 57.76 | 64.19 | 76.65 | — | 92.29 | 2.80 |
all-docs (anuj1541/indictrans2-all-docs) | 70.56 | 72.38 | 74.41 | 60.22 | — | 93.58 | 3.14 |
| fine-tuned (this repo) | 49.05 | 65.92 | 74.47 | 73.91 | — | 93.66 | 3.20 |