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---
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
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