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ethiopic-asr-characters

Automatic Speech Recognition
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End of training

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Files changed (3) hide show
  1. README.md +26 -13
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 0.3384350075447295
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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
@@ -32,9 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.5343
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- - Wer: 0.3384
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- - Phoneme Cer: 0.1545
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  ## Model description
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@@ -60,20 +60,33 @@ The following hyperparameters were used during training:
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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: 2
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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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- | 0.458 | 0.2312 | 200 | 0.6372 | 0.3657 | 0.1651 |
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- | 0.3523 | 0.4624 | 400 | 0.6086 | 0.3552 | 0.1613 |
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- | 0.2547 | 0.6936 | 600 | 0.5896 | 0.3466 | 0.1581 |
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- | 0.2305 | 0.9249 | 800 | 0.5750 | 0.3450 | 0.1578 |
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- | 0.1565 | 1.1561 | 1000 | 0.5597 | 0.3405 | 0.1563 |
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- | 0.3241 | 1.3873 | 1200 | 0.5558 | 0.3393 | 0.1555 |
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- | 0.2219 | 1.6185 | 1400 | 0.5439 | 0.3399 | 0.1553 |
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- | 0.2741 | 1.8497 | 1600 | 0.5343 | 0.3384 | 0.1545 |
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 0.3037292519939642
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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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  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: 0.4233
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+ - Wer: 0.3037
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+ - Phoneme Cer: 0.1439
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  ## Model description
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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: 5
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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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+ | 0.1902 | 0.2312 | 200 | 0.5678 | 0.3431 | 0.1555 |
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+ | 0.1622 | 0.4624 | 400 | 0.5520 | 0.3321 | 0.1532 |
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+ | 0.0933 | 0.6936 | 600 | 0.5467 | 0.3292 | 0.1527 |
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+ | 0.1337 | 0.9249 | 800 | 0.5601 | 0.3315 | 0.1531 |
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+ | 0.091 | 1.1561 | 1000 | 0.5508 | 0.3307 | 0.1522 |
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+ | 0.2286 | 1.3873 | 1200 | 0.5274 | 0.3267 | 0.1510 |
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+ | 0.1596 | 1.6185 | 1400 | 0.5085 | 0.3273 | 0.1506 |
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+ | 0.2091 | 1.8497 | 1600 | 0.4826 | 0.3198 | 0.1498 |
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+ | 0.2798 | 2.0809 | 1800 | 0.4731 | 0.3187 | 0.1489 |
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+ | 0.2678 | 2.3121 | 2000 | 0.4700 | 0.3165 | 0.1482 |
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+ | 0.2777 | 2.5434 | 2200 | 0.4521 | 0.3137 | 0.1468 |
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+ | 0.5036 | 2.7746 | 2400 | 0.4592 | 0.3133 | 0.1463 |
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+ | 0.3513 | 3.0058 | 2600 | 0.4535 | 0.3119 | 0.1469 |
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+ | 0.6127 | 3.2370 | 2800 | 0.4434 | 0.3080 | 0.1457 |
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+ | 0.3057 | 3.4682 | 3000 | 0.4377 | 0.3090 | 0.1454 |
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+ | 0.346 | 3.6994 | 3200 | 0.4348 | 0.3077 | 0.1449 |
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+ | 0.3782 | 3.9306 | 3400 | 0.4273 | 0.3035 | 0.1442 |
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+ | 0.2468 | 4.1618 | 3600 | 0.4270 | 0.3051 | 0.1442 |
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+ | 0.1932 | 4.3931 | 3800 | 0.4232 | 0.3029 | 0.1436 |
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+ | 0.3175 | 4.6243 | 4000 | 0.4269 | 0.3040 | 0.1435 |
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+ | 0.1834 | 4.8555 | 4200 | 0.4233 | 0.3037 | 0.1439 |
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  ### Framework versions
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