---
library_name: peft
license: cc-by-nc-4.0
base_model: facebook/nllb-200-distilled-600M
tags:
- generated_from_trainer
model-index:
- name: druk-ai-20250628_0745
  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. -->

# druk-ai-20250628_0745

This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2690

## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.6718        | 0.0684 | 50   | 3.9966          |
| 3.3909        | 0.1367 | 100  | 3.2014          |
| 3.2175        | 0.2051 | 150  | 2.9763          |
| 3.1066        | 0.2734 | 200  | 2.9230          |
| 3.058         | 0.3418 | 250  | 2.8082          |
| 2.9733        | 0.4101 | 300  | 2.7560          |
| 2.9797        | 0.4785 | 350  | 2.7420          |
| 2.714         | 0.5468 | 400  | 2.6686          |
| 2.8964        | 0.6152 | 450  | 2.6501          |
| 2.7973        | 0.6835 | 500  | 2.6197          |
| 2.7552        | 0.7519 | 550  | 2.5710          |
| 2.7453        | 0.8202 | 600  | 2.5410          |
| 2.9687        | 0.8886 | 650  | 2.5268          |
| 2.7995        | 0.9569 | 700  | 2.5237          |
| 2.5497        | 1.0253 | 750  | 2.5099          |
| 2.6585        | 1.0936 | 800  | 2.4769          |
| 2.7442        | 1.1620 | 850  | 2.4660          |
| 2.7224        | 1.2303 | 900  | 2.4511          |
| 2.704         | 1.2987 | 950  | 2.4375          |
| 2.5466        | 1.3671 | 1000 | 2.4223          |
| 2.3552        | 1.4354 | 1050 | 2.4044          |
| 2.6877        | 1.5038 | 1100 | 2.4021          |
| 2.2772        | 1.5721 | 1150 | 2.3974          |
| 2.5707        | 1.6405 | 1200 | 2.3753          |
| 2.5388        | 1.7088 | 1250 | 2.3624          |
| 2.4451        | 1.7772 | 1300 | 2.3741          |
| 2.6623        | 1.8455 | 1350 | 2.3595          |
| 2.2503        | 1.9139 | 1400 | 2.3445          |
| 2.4205        | 1.9822 | 1450 | 2.3315          |
| 2.2562        | 2.0506 | 1500 | 2.3277          |
| 2.2127        | 2.1189 | 1550 | 2.3287          |
| 2.4043        | 2.1873 | 1600 | 2.3091          |
| 2.3461        | 2.2556 | 1650 | 2.3168          |
| 2.5133        | 2.3240 | 1700 | 2.2984          |
| 2.4444        | 2.3923 | 1750 | 2.2961          |
| 2.3056        | 2.4607 | 1800 | 2.2970          |
| 2.4537        | 2.5290 | 1850 | 2.2844          |
| 2.3241        | 2.5974 | 1900 | 2.2835          |
| 2.2608        | 2.6658 | 1950 | 2.2756          |
| 2.3779        | 2.7341 | 2000 | 2.2758          |
| 2.3757        | 2.8025 | 2050 | 2.2691          |
| 2.2582        | 2.8708 | 2100 | 2.2710          |
| 2.3975        | 2.9392 | 2150 | 2.2690          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.0
- Pytorch 2.6.0+cu124
- Datasets 2.21.0
- Tokenizers 0.20.3