mms-1b-all-bemgen-combined-m50f50-42-DAT-0.5
This model is a fine-tuned version of facebook/mms-1b-all on the BEMGEN - BEM dataset. It achieves the following results on the evaluation set:
- Loss: 0.2685
- Cer: 0.0768
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 30.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Cer |
---|---|---|---|---|
8.7038 | 0.8439 | 100 | 2.9604 | 1.0000 |
2.896 | 1.6835 | 200 | 1.1561 | 0.3748 |
1.6872 | 2.5232 | 300 | 0.3652 | 0.1080 |
1.3958 | 3.3629 | 400 | 0.3356 | 0.0984 |
1.3331 | 4.2025 | 500 | 0.3044 | 0.0873 |
1.2736 | 5.0422 | 600 | 0.2927 | 0.0829 |
1.2319 | 5.8861 | 700 | 0.2865 | 0.0818 |
1.2493 | 6.7257 | 800 | 0.2809 | 0.0798 |
1.162 | 7.5654 | 900 | 0.2779 | 0.0789 |
1.2392 | 8.4051 | 1000 | 0.2759 | 0.0786 |
1.2305 | 9.2447 | 1100 | 0.2718 | 0.0760 |
1.1666 | 10.0844 | 1200 | 0.2686 | 0.0768 |
1.1685 | 10.9283 | 1300 | 0.2668 | 0.0738 |
1.158 | 11.7679 | 1400 | 0.2667 | 0.0742 |
1.1767 | 12.6076 | 1500 | 0.2628 | 0.0736 |
1.1855 | 13.4473 | 1600 | 0.2646 | 0.0749 |
1.1381 | 14.2869 | 1700 | 0.2662 | 0.0740 |
1.14 | 15.1266 | 1800 | 0.2656 | 0.0749 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0
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Model tree for csikasote/mms-1b-all-bemgen-combined-m50f50-42-DAT-0.5
Base model
facebook/mms-1b-all