mms-1b-all-bemgen-combined-m50f50-52-DAT-0.1-fusion
This model is a fine-tuned version of facebook/mms-1b-all on the BEMGEN - DEB dataset. It achieves the following results on the evaluation set:
- Loss: 0.5413
- Cer: 0.1935
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 |
---|---|---|---|---|
3.1278 | 0.8439 | 100 | 3.0679 | 1.0000 |
2.0297 | 1.6835 | 200 | 2.0047 | 0.7660 |
0.9209 | 2.5232 | 300 | 0.7206 | 0.2297 |
0.5360 | 3.3629 | 400 | 0.5413 | 0.1935 |
0.5060 | 4.2025 | 500 | 0.4814 | 0.1778 |
0.3886 | 5.0422 | 600 | 0.4299 | 0.1601 |
0.4715 | 5.8861 | 700 | 0.4831 | 0.1796 |
0.4244 | 6.7257 | 800 | 0.4628 | 0.1724 |
0.4904 | 7.5654 | 900 | 0.4543 | 0.1764 |
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-0.1-fusion
Base model
facebook/mms-1b-all