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Mamadou2727
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nllb-fr-dje

Text2Text Generation
Transformers
Safetensors
m2m_100
Generated from Trainer
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End of training

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  1. README.md +11 -7
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4331
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- - Bleu: 27.0215
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  ## Model description
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@@ -45,17 +45,21 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 64
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 4
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|
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- | 2.8664 | 1.0 | 508 | 1.8497 | 20.6335 |
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- | 1.7995 | 2.0 | 1017 | 1.5528 | 25.3333 |
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- | 1.5732 | 3.0 | 1526 | 1.4589 | 26.7125 |
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- | 1.4864 | 3.99 | 2032 | 1.4331 | 27.0215 |
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2285
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+ - Bleu: 29.6795
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  ## Model description
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  - total_train_batch_size: 64
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 8
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|
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+ | 2.8423 | 1.0 | 508 | 1.8073 | 20.0301 |
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+ | 1.7444 | 2.0 | 1017 | 1.4882 | 25.3031 |
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+ | 1.4902 | 3.0 | 1526 | 1.3685 | 27.3325 |
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+ | 1.3532 | 4.0 | 2035 | 1.3004 | 28.0924 |
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+ | 1.2749 | 5.0 | 2544 | 1.2632 | 29.0171 |
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+ | 1.2153 | 6.0 | 3053 | 1.2432 | 29.3495 |
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+ | 1.1793 | 7.0 | 3562 | 1.2323 | 29.5367 |
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+ | 1.1548 | 7.99 | 4064 | 1.2285 | 29.6795 |
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  ### Framework versions
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