File size: 2,352 Bytes
7af68b7 e8ec778 157fa2b 7af68b7 e8ec778 7af68b7 e8ec778 7af68b7 e8ec778 7af68b7 e8ec778 9cc2a63 e8ec778 7af68b7 e8ec778 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/nllb-200-distilled-600M
tags:
- generated_from_trainer
model-index:
- name: nllb-indo-en-cleaned
results: []
datasets:
- cobrayyxx/FLEURS_INDO-ENG_Speech_Translation_No_Duplicate
language:
- id
- en
metrics:
- bleu
- chrf
pipeline_tag: audio-text-to-text
---
<!-- 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-indo-en
This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on [Fleurs Dataset](https://huggingface.co/datasets/cobrayyxx/FLEURS_INDO-ENG_Speech_Translation_No_Duplicate) without duplication of `id`s.
It achieves the following results on the evaluation set:
- Loss: 0.3048
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| No log | 1.0 | 96 | 4.3318 |
| 53.1274 | 2.0 | 192 | 2.0475 |
| 25.7634 | 3.0 | 288 | 0.4936 |
| 8.4388 | 4.0 | 384 | 0.2444 |
| 1.7896 | 5.0 | 480 | 0.2407 |
| 0.8853 | 6.0 | 576 | 0.2626 |
| 0.5583 | 7.0 | 672 | 0.2793 |
| 0.4353 | 8.0 | 768 | 0.2936 |
| 0.3497 | 9.0 | 864 | 0.2992 |
| 0.2969 | 10.0 | 960 | 0.3038 |
| 0.2713 | 10.4199 | 1000 | 0.3048 |
## Model Evaluation
The performance of this model was evaluated using BLEU and CHRF metrics on validation dataset.
| BLEU | CHRF |
|:----:|:-----:|
| 40.94| 66.46 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0 |