| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: Samuael/geez-asr |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - alffa_amharic |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: ethiopic-asr |
| | results: |
| | - task: |
| | type: automatic-speech-recognition |
| | name: Automatic Speech Recognition |
| | dataset: |
| | name: alffa_amharic |
| | type: alffa_amharic |
| | config: clean |
| | split: None |
| | args: clean |
| | metrics: |
| | - type: wer |
| | value: 0.14692601597777005 |
| | name: Wer |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # ethiopic-asr |
| |
|
| | This model is a fine-tuned version of [Samuael/geez-asr](https://huggingface.co/Samuael/geez-asr) on the alffa_amharic dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1301 |
| | - Wer: 0.1469 |
| | - Phoneme Cer: 0.0296 |
| | - Cer: 0.0416 |
| | |
| | ## 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: 3e-05 |
| | - train_batch_size: 8 |
| | - 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: 100 |
| | - num_epochs: 1 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Wer | Phoneme Cer | Cer | |
| | |:-------------:|:------:|:----:|:---------------:|:------:|:-----------:|:------:| |
| | | No log | 0.0442 | 200 | 3.2216 | 1.0 | 1.0 | 1.0 | |
| | | No log | 0.0883 | 400 | 3.1164 | 1.0 | 1.0 | 1.0 | |
| | | 4.1769 | 0.1325 | 600 | 0.9628 | 0.5476 | 0.1141 | 0.1609 | |
| | | 4.1769 | 0.1767 | 800 | 0.3181 | 0.2150 | 0.0430 | 0.0607 | |
| | | 0.8455 | 0.2208 | 1000 | 0.2195 | 0.1759 | 0.0353 | 0.0503 | |
| | | 0.8455 | 0.2650 | 1200 | 0.1913 | 0.1846 | 0.0365 | 0.0520 | |
| | | 0.8455 | 0.3092 | 1400 | 0.1699 | 0.1591 | 0.0322 | 0.0454 | |
| | | 0.2929 | 0.3534 | 1600 | 0.1603 | 0.1572 | 0.0316 | 0.0442 | |
| | | 0.2929 | 0.3975 | 1800 | 0.1503 | 0.1567 | 0.0315 | 0.0442 | |
| | | 0.2392 | 0.4417 | 2000 | 0.1476 | 0.1587 | 0.0318 | 0.0446 | |
| | | 0.2392 | 0.4859 | 2200 | 0.1449 | 0.1565 | 0.0312 | 0.0438 | |
| | | 0.2392 | 0.5300 | 2400 | 0.1409 | 0.1537 | 0.0308 | 0.0427 | |
| | | 0.2166 | 0.5742 | 2600 | 0.1395 | 0.1551 | 0.0308 | 0.0428 | |
| | | 0.2166 | 0.6184 | 2800 | 0.1345 | 0.1469 | 0.0290 | 0.0410 | |
| | | 0.2068 | 0.6625 | 3000 | 0.1331 | 0.1509 | 0.0297 | 0.0419 | |
| | | 0.2068 | 0.7067 | 3200 | 0.1346 | 0.1518 | 0.0301 | 0.0421 | |
| | | 0.2068 | 0.7509 | 3400 | 0.1335 | 0.1507 | 0.0303 | 0.0426 | |
| | | 0.2037 | 0.7951 | 3600 | 0.1312 | 0.1471 | 0.0297 | 0.0415 | |
| | | 0.2037 | 0.8392 | 3800 | 0.1303 | 0.1438 | 0.0289 | 0.0406 | |
| | | 0.1985 | 0.8834 | 4000 | 0.1300 | 0.1457 | 0.0292 | 0.0410 | |
| | | 0.1985 | 0.9276 | 4200 | 0.1303 | 0.1471 | 0.0295 | 0.0414 | |
| | | 0.1985 | 0.9717 | 4400 | 0.1301 | 0.1469 | 0.0296 | 0.0416 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.45.1 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.0.1 |
| | - Tokenizers 0.20.0 |
| |
|
