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en-ne – Dataset by BeebekBhz | AlphaNeural AI
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en-ne
This model is a fine-tuned version of
Helsinki-NLP/opus-mt-en-hi
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 1.3328
Validation Loss: 1.5832
Epoch: 5
Model description
More information needed
Intended uses & limitations
More information needed
BLEU Score
The model achieves a BLEU score of
14.83
on the
test
split of the
BeebekBhz/en-ne
dataset.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32
Training results
Train Loss
Validation Loss
Epoch
2.6327
2.0059
0
1.9273
1.7883
1
1.6957
1.6886
2
1.5456
1.6348
3
1.4287
1.6065
4
1.3328
1.5832
5
Framework versions
Transformers 4.47.1
TensorFlow 2.17.1
Datasets 3.3.2
Tokenizers 0.21.0
