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languagemodel
This model is a fine-tuned version of monideep2255/XLRS-torgo on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 1.1173
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.3015 | 3.12 | 400 | inf | 1.3984 |
| 0.6892 | 6.25 | 800 | inf | 1.1059 |
| 0.5069 | 9.37 | 1200 | inf | 1.0300 |
| 0.3596 | 12.5 | 1600 | inf | 1.0830 |
| 0.2571 | 15.62 | 2000 | inf | 1.1981 |
| 0.198 | 18.75 | 2400 | inf | 1.1009 |
| 0.1523 | 21.87 | 2800 | inf | 1.1803 |
| 0.1112 | 25.0 | 3200 | inf | 1.0429 |
| 0.08 | 28.12 | 3600 | inf | 1.1173 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.13.1
