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CV30_finetuning
This model is a fine-tuned version of Roshana/CV11_finetuning1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7956
- Wer: 0.3677
- Cer: 0.1436
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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
0.1203 | 0.86 | 400 | 0.7747 | 0.4192 | 0.1656 |
0.2191 | 1.72 | 800 | 0.7546 | 0.4356 | 0.1771 |
0.213 | 2.59 | 1200 | 0.6965 | 0.4276 | 0.1709 |
0.1858 | 3.45 | 1600 | 0.7189 | 0.4156 | 0.1673 |
0.1597 | 4.31 | 2000 | 0.7462 | 0.4031 | 0.1606 |
0.1398 | 5.17 | 2400 | 0.7622 | 0.3944 | 0.1584 |
0.1245 | 6.03 | 2800 | 0.7527 | 0.3917 | 0.1553 |
0.1035 | 6.9 | 3200 | 0.7347 | 0.3819 | 0.1532 |
0.0918 | 7.76 | 3600 | 0.7825 | 0.3786 | 0.1497 |
0.0767 | 8.62 | 4000 | 0.7909 | 0.3724 | 0.1444 |
0.0722 | 9.48 | 4400 | 0.7956 | 0.3677 | 0.1436 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2