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med_v1_M01
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Cer: 0.8926
- Loss: 3.2885
- Wer: 1.0
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: 0.0001
- train_batch_size: 20
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 13500
- num_epochs: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|---|---|---|---|---|---|
| 16.9472 | 200.0 | 27000 | 0.9041 | 3.2161 | 1.0 |
| 2.6444 | 400.0 | 54000 | 0.8959 | 3.2246 | 1.0 |
| 2.5434 | 600.0 | 81000 | 0.8942 | 3.2352 | 1.0 |
| 2.4925 | 800.0 | 108000 | 0.8959 | 3.2468 | 1.0 |
| 2.4631 | 1000.0 | 135000 | 0.8942 | 3.2656 | 1.0 |
| 2.4434 | 1200.0 | 162000 | 0.8942 | 3.2616 | 1.0 |
| 2.4292 | 1400.0 | 189000 | 0.8942 | 3.2840 | 1.0 |
| 2.4203 | 1600.0 | 216000 | 0.8926 | 3.2791 | 1.0 |
| 2.4148 | 1800.0 | 243000 | 0.8926 | 3.2866 | 1.0 |
| 2.4112 | 2000.0 | 270000 | 0.8926 | 3.2885 | 1.0 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.2+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
