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ethiopic-asr-characters

Automatic Speech Recognition
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wav2vec2
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End of training

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Files changed (3) hide show
  1. README.md +22 -26
  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: 0.3037292519939642
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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
@@ -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: 0.4233
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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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@@ -60,33 +60,29 @@ 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: 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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  metrics:
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  - name: Wer
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  type: wer
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+ value: 0.29963354171157575
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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: 0.4428
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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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  - 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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