---
license: cc-by-nc-4.0
base_model: facebook/nllb-200-1.3B
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: Terjman-Ultra
  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. -->

# Terjman-Ultra

This model is a fine-tuned version of [facebook/nllb-200-1.3B](https://huggingface.co/facebook/nllb-200-1.3B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7070
- Bleu: 4.6998
- Gen Len: 35.6088

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 25

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:-------:|
| 3.203         | 0.9999  | 2242  | 2.9015          | 4.3057 | 36.7548 |
| 2.9175        | 1.9998  | 4484  | 2.7602          | 4.4286 | 35.708  |
| 2.8558        | 2.9997  | 6726  | 2.7303          | 4.629  | 35.562  |
| 2.8696        | 4.0     | 8969  | 2.7195          | 4.6537 | 35.562  |
| 2.8604        | 4.9999  | 11211 | 2.7144          | 4.6905 | 35.5702 |
| 2.8509        | 5.9998  | 13453 | 2.7112          | 4.599  | 35.5427 |
| 2.853         | 6.9997  | 15695 | 2.7098          | 4.6625 | 35.5317 |
| 2.8475        | 8.0     | 17938 | 2.7081          | 4.6901 | 35.6419 |
| 2.8192        | 8.9999  | 20180 | 2.7082          | 4.5474 | 35.6391 |
| 2.8395        | 9.9998  | 22422 | 2.7077          | 4.722  | 35.6088 |
| 2.8395        | 10.9997 | 24664 | 2.7076          | 4.752  | 35.5868 |
| 2.8362        | 12.0    | 26907 | 2.7074          | 4.6664 | 35.562  |
| 2.8673        | 12.9999 | 29149 | 2.7072          | 4.7004 | 35.6639 |
| 2.8465        | 13.9998 | 31391 | 2.7076          | 4.6715 | 35.5923 |
| 2.8281        | 14.9997 | 33633 | 2.7075          | 4.7045 | 35.5647 |
| 2.8191        | 16.0    | 35876 | 2.7068          | 4.7487 | 35.6253 |
| 2.874         | 16.9999 | 38118 | 2.7076          | 4.71   | 35.6006 |
| 2.8666        | 17.9998 | 40360 | 2.7069          | 4.6047 | 35.6281 |
| 2.8645        | 18.9997 | 42602 | 2.7063          | 4.6664 | 35.6088 |
| 2.8458        | 20.0    | 44845 | 2.7070          | 4.6552 | 35.5813 |
| 2.8501        | 20.9999 | 47087 | 2.7074          | 4.6919 | 35.5647 |
| 2.8309        | 21.9998 | 49329 | 2.7074          | 4.623  | 35.6226 |
| 2.854         | 22.9997 | 51571 | 2.7072          | 4.6495 | 35.5978 |
| 2.8407        | 24.0    | 53814 | 2.7070          | 4.6879 | 35.5482 |
| 2.8129        | 24.9972 | 56050 | 2.7070          | 4.6998 | 35.6088 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1