opus-mt-ar-en-finetuned_augmented_synthetic_1-ar-to-en – AI Model by Jezia | AlphaNeural AI

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Jezia/
opus-mt-ar-en-finetuned_augmented_synthetic_1-ar-to-en

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text2text-generation

generated_from_trainer

Helsinki-NLP/opus-mt-ar-en

endpoints_compatible

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opus-mt-ar-en-finetuned_augmented_synthetic_1-ar-to-en

This model is a fine-tuned version of Helsinki-NLP/opus-mt-ar-en on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6310
Bleu: 66.0531
Gen Len: 62.7622

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
0.9624	1.0	1043	0.7904	57.9585	65.1449
0.7619	2.0	2086	0.7172	61.4081	64.038
0.674	3.0	3129	0.6844	63.0849	63.1159
0.6086	4.0	4172	0.6626	64.6547	62.3736
0.5705	5.0	5215	0.6523	65.1199	62.7662
0.5317	6.0	6258	0.6415	65.6392	62.7802
0.4943	7.0	7301	0.6367	65.4163	62.5654
0.4828	8.0	8344	0.6340	65.4508	62.3506
0.4579	9.0	9387	0.6317	65.8711	62.6513
0.4577	10.0	10430	0.6310	66.0531	62.7622

Framework versions

Transformers 4.32.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3