mms-1b-all-bemgen-combined-m50f50-52-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: 0.2687
- Cer: 0.0762
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: 52
- 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 |
---|---|---|---|---|
7.5249 | 0.8439 | 100 | 2.8759 | 0.9925 |
2.5604 | 1.6835 | 200 | 0.5393 | 0.1710 |
1.5275 | 2.5232 | 300 | 0.3629 | 0.1072 |
1.3518 | 3.3629 | 400 | 0.3246 | 0.0949 |
1.218 | 4.2025 | 500 | 0.3083 | 0.0895 |
1.2951 | 5.0422 | 600 | 0.2886 | 0.0838 |
1.2115 | 5.8861 | 700 | 0.2859 | 0.0827 |
1.2352 | 6.7257 | 800 | 0.2849 | 0.0814 |
1.2512 | 7.5654 | 900 | 0.2735 | 0.0782 |
1.1716 | 8.4051 | 1000 | 0.2759 | 0.0775 |
1.2454 | 9.2447 | 1100 | 0.2692 | 0.0750 |
1.1644 | 10.0844 | 1200 | 0.2687 | 0.0762 |
1.1234 | 10.9283 | 1300 | 0.2658 | 0.0745 |
1.1794 | 11.7679 | 1400 | 0.2677 | 0.0753 |
1.1293 | 12.6076 | 1500 | 0.2669 | 0.0746 |
1.1625 | 13.4473 | 1600 | 0.2686 | 0.0736 |
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-m50f50-52-DAT-0.5
Base model
facebook/mms-1b-all