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--- |
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library_name: transformers |
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base_model: Samuael/ethiopic-asr-characters |
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tags: |
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- generated_from_trainer |
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datasets: |
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- alffa_amharic |
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metrics: |
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- wer |
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model-index: |
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- name: ethiopic-asr-characters |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: alffa_amharic |
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type: alffa_amharic |
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config: clean |
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split: None |
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args: clean |
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metrics: |
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- type: wer |
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value: 0.29963354171157575 |
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name: Wer |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ethiopic-asr-characters |
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This model is a fine-tuned version of [Samuael/ethiopic-asr-characters](https://huggingface.co/Samuael/ethiopic-asr-characters) on the alffa_amharic dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4428 |
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- Wer: 0.2996 |
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- Phoneme Cer: 0.1421 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Phoneme Cer | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:-----------:| |
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| 0.1559 | 0.2312 | 200 | 0.5540 | 0.3212 | 0.1475 | |
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| 0.1228 | 0.4624 | 400 | 0.5394 | 0.3142 | 0.1466 | |
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| 0.069 | 0.6936 | 600 | 0.5525 | 0.3139 | 0.1466 | |
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| 0.0997 | 0.9249 | 800 | 0.5531 | 0.3118 | 0.1462 | |
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| 0.0732 | 1.1561 | 1000 | 0.5644 | 0.3196 | 0.1465 | |
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| 0.1637 | 1.3873 | 1200 | 0.5367 | 0.3185 | 0.1468 | |
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| 0.1145 | 1.6185 | 1400 | 0.5215 | 0.3180 | 0.1468 | |
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| 0.1499 | 1.8497 | 1600 | 0.4985 | 0.3141 | 0.1455 | |
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| 0.1975 | 2.0809 | 1800 | 0.4814 | 0.3114 | 0.1446 | |
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| 0.2116 | 2.3121 | 2000 | 0.4855 | 0.3085 | 0.1446 | |
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| 0.2384 | 2.5434 | 2200 | 0.4702 | 0.3083 | 0.1441 | |
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| 0.4346 | 2.7746 | 2400 | 0.4762 | 0.3063 | 0.1435 | |
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| 0.3156 | 3.0058 | 2600 | 0.4677 | 0.3044 | 0.1432 | |
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| 0.5558 | 3.2370 | 2800 | 0.4574 | 0.2993 | 0.1425 | |
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| 0.2787 | 3.4682 | 3000 | 0.4478 | 0.2989 | 0.1420 | |
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| 0.3268 | 3.6994 | 3200 | 0.4466 | 0.2978 | 0.1418 | |
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| 0.3461 | 3.9306 | 3400 | 0.4428 | 0.2996 | 0.1421 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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