h6_f1536_l16_d384_trained
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0269
- Per Phonemes: 0.0104
- Per Hams Or Jahr: 0.0257
- Per Shidda Or Rakhawa: 0.0079
- Per Tafkheem Or Taqeeq: 0.0043
- Per Itbaq: 0.0120
- Per Safeer: 0.0076
- Per Qalqla: 0.0053
- Per Tikraar: 0.0142
- Per Tafashie: 0.0027
- Per Istitala: 0.0030
- Per Ghonna: 0.0053
- Average Per: 0.0090
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: 5e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- 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: constant
- lr_scheduler_warmup_steps: 0.2
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Per Phonemes | Per Hams Or Jahr | Per Shidda Or Rakhawa | Per Tafkheem Or Taqeeq | Per Itbaq | Per Safeer | Per Qalqla | Per Tikraar | Per Tafashie | Per Istitala | Per Ghonna | Average Per |
|---|
| 0.7398 | 1.0 | 19409 | 0.1096 | 0.0397 | 0.0784 | 0.0330 | 0.0190 | 0.0226 | 0.0296 | 0.0120 | 0.0307 | 0.0089 | 0.0093 | 0.0175 | 0.0273 |
| 0.0807 | 2.0 | 38818 | 0.0588 | 0.0224 | 0.0417 | 0.0169 | 0.0094 | 0.0095 | 0.0109 | 0.0065 | 0.0107 | 0.0051 | 0.0053 | 0.0097 | 0.0135 |
| 0.0501 | 3.0 | 58227 | 0.0428 | 0.0166 | 0.0346 | 0.0122 | 0.0069 | 0.0070 | 0.0067 | 0.0048 | 0.0102 | 0.0035 | 0.0038 | 0.0075 | 0.0103 |
| 0.0369 | 4.0 | 77636 | 0.0340 | 0.0126 | 0.0258 | 0.0101 | 0.0056 | 0.0060 | 0.0055 | 0.0043 | 0.0083 | 0.0030 | 0.0034 | 0.0061 | 0.0082 |
| 0.0294 | 5.0 | 97045 | 0.0269 | 0.0104 | 0.0257 | 0.0079 | 0.0043 | 0.0120 | 0.0076 | 0.0053 | 0.0142 | 0.0027 | 0.0030 | 0.0053 | 0.0090 |
Framework versions
- Transformers 5.9.0
- Pytorch 2.12.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2