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Nllb Indo En

This model is a fine-tuned version of facebook/nllb-200-distilled-600M on Fleurs Dataset without duplication of ids. It achieves the following results on the evaluation set: Loss: 0.3048

Fuentehuggingface.co/cobrayyxx/nllb-indo-en/tree/9cc2a63ee670a4fcaff03679f7a89e240cc19595
TipoText modelModelo basefacebook/nllb-200-distilled-600MVersiónFP32Bcalidad

Fuente del modelo

Tipo
Text model
Tamaño del archivo
2,29 GB
Modelo base
facebook/nllb-200-distilled-600M
Versión
vFP32
Actualizado
31 oct 2026
Descargas
41
Fuente
Hugging Face

Descripción de la fuente

nllb-indo-en

This model is a fine-tuned version of facebook/nllb-200-distilled-600M on Fleurs Dataset without duplication of ids. 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 LossEpochStepValidation Loss
No log1.0964.3318
53.12742.01922.0475
25.76343.02880.4936
8.43884.03840.2444
1.78965.04800.2407
0.88536.05760.2626
0.55837.06720.2793
0.43538.07680.2936
0.34979.08640.2992
0.296910.09600.3038
0.271310.419910000.3048

Model Evaluation

The performance of this model was evaluated using BLEU and CHRF metrics on validation dataset.

BLEUCHRF
40.9466.46

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0

Fuentes

1 fuente
Hugging FacePrincipalVersión 9cc2a63ee670a4fcaff03679f7a89e240cc19595
huggingface.co/cobrayyxx/nllb-indo-en/tree/9cc2a63ee670a4fcaff03679f7a89e240cc19595

Verificado 31 oct

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Artefactos del modelo

1 artefacto

model.safetensors

safetensors · FP32 (unverified) · 2,29 GB · SHA-256 83e9a6803b15…bc24 · Hugging Face

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Extractos de fuentes

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Readme15 agohuggingface.co/cobrayyxx/nllb-indo-en

--- 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

Note31 octhuggingface.co/cobrayyxx/nllb-indo-en

Source context: 41 downloads · 0 likes · Pipeline audio-text-to-text · Library transformers · Repo cobrayyxx/nllb-indo-en

Note15 agohuggingface.co/cobrayyxx/nllb-indo-en

Source context: 9 downloads · 0 likes · Pipeline audio-text-to-text · Library transformers · Repo cobrayyxx/nllb-indo-en