Terjman-Large-v2
This model is a fine-tuned version of Helsinki-NLP/opus-mt-tc-big-en-ar on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.9483
- Bleu: 0.0891
- Gen Len: 511.0
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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
---|---|---|---|---|---|
12.4538 | 0.1449 | 1000 | 6.3599 | 0.0191 | 511.0 |
12.5456 | 0.2899 | 2000 | 6.7320 | 0.0026 | 499.9054 |
12.0592 | 0.4348 | 3000 | 6.2157 | 0.0097 | 511.0 |
11.8591 | 0.5798 | 4000 | 6.1470 | 0.0269 | 511.0 |
11.776 | 0.7247 | 5000 | 6.0090 | 0.0469 | 511.0 |
11.3534 | 0.8696 | 6000 | 5.9483 | 0.0891 | 511.0 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0
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Base model
Helsinki-NLP/opus-mt-tc-big-en-ar