NLLB_LoRA / README.md
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finetune-NLLB-600M-on-opus100-Ar2En-with-lora
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---
base_model: facebook/nllb-200-distilled-600M
library_name: peft
license: cc-by-nc-4.0
metrics:
- bleu
- rouge
tags:
- generated_from_trainer
model-index:
- name: NLLB_LoRA
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. -->
# NLLB_LoRA
This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3291
- Bleu: 32.6379
- Rouge: 0.5923
- Gen Len: 17.375
## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 2.714 | 1.0 | 875 | 1.3916 | 31.9042 | 0.5851 | 17.4015 |
| 1.457 | 2.0 | 1750 | 1.3379 | 32.3993 | 0.5916 | 17.4175 |
| 1.4281 | 3.0 | 2625 | 1.3291 | 32.6379 | 0.5923 | 17.375 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1