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---
library_name: peft
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-en-mr
tags:
- generated_from_trainer
model-index:
- name: english-marathi-colloquial-translator-updated
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. -->
# english-marathi-colloquial-translator-updated
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-mr](https://huggingface.co./Helsinki-NLP/opus-mt-en-mr) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6189
## 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 0.5693 | 0.08 | 500 | 0.6740 |
| 0.8813 | 0.16 | 1000 | 0.6623 |
| 0.4563 | 0.24 | 1500 | 0.6546 |
| 0.306 | 0.32 | 2000 | 0.6500 |
| 0.4356 | 0.4 | 2500 | 0.6460 |
| 0.9248 | 0.48 | 3000 | 0.6441 |
| 0.5172 | 0.56 | 3500 | 0.6410 |
| 0.6833 | 0.64 | 4000 | 0.6391 |
| 0.6665 | 0.72 | 4500 | 0.6365 |
| 0.6056 | 0.8 | 5000 | 0.6360 |
| 0.7969 | 0.88 | 5500 | 0.6338 |
| 1.0205 | 0.96 | 6000 | 0.6325 |
| 0.7191 | 1.04 | 6500 | 0.6312 |
| 0.7727 | 1.12 | 7000 | 0.6300 |
| 0.7991 | 1.2 | 7500 | 0.6287 |
| 0.4923 | 1.28 | 8000 | 0.6286 |
| 0.4553 | 1.3600 | 8500 | 0.6270 |
| 0.9829 | 1.44 | 9000 | 0.6265 |
| 0.8621 | 1.52 | 9500 | 0.6257 |
| 0.6201 | 1.6 | 10000 | 0.6242 |
| 0.9138 | 1.6800 | 10500 | 0.6234 |
| 0.5501 | 1.76 | 11000 | 0.6233 |
| 0.7267 | 1.8400 | 11500 | 0.6232 |
| 0.7323 | 1.92 | 12000 | 0.6223 |
| 1.0083 | 2.0 | 12500 | 0.6222 |
| 0.3809 | 2.08 | 13000 | 0.6220 |
| 0.9979 | 2.16 | 13500 | 0.6214 |
| 0.5853 | 2.24 | 14000 | 0.6211 |
| 0.6319 | 2.32 | 14500 | 0.6207 |
| 0.7518 | 2.4 | 15000 | 0.6206 |
| 0.6834 | 2.48 | 15500 | 0.6198 |
| 0.246 | 2.56 | 16000 | 0.6198 |
| 0.5533 | 2.64 | 16500 | 0.6194 |
| 0.5569 | 2.7200 | 17000 | 0.6193 |
| 0.5367 | 2.8 | 17500 | 0.6189 |
| 0.5825 | 2.88 | 18000 | 0.6189 |
| 0.8336 | 2.96 | 18500 | 0.6189 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0 |