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jethrowang
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webcam_loss_CH_0.5_emb-whisper-tiny

Automatic Speech Recognition
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Safetensors
Chinese
whisper
Generated from Trainer
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End of training

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  1. README.md +25 -25
  2. model.safetensors +1 -1
  3. runs/Aug13_16-20-46_nv3090/events.out.tfevents.1723537250.nv3090.204371.0 +2 -2
README.md CHANGED
@@ -8,19 +8,19 @@ tags:
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  datasets:
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  - formospeech/hat_asr_aligned
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  model-index:
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- - name: Whisper Tiny Hakka Condenser
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  results: []
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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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- # Whisper Tiny Hakka Condenser
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the HAT ASR Aligned dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1966
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- - Cer: 12.4315
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  ## Model description
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@@ -39,7 +39,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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  - train_batch_size: 64
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  - eval_batch_size: 32
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  - seed: 42
@@ -53,26 +53,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Cer |
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  |:-------------:|:-------:|:----:|:---------------:|:-------:|
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- | 1.161 | 0.9980 | 488 | 1.1833 | 47.8084 |
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- | 0.3742 | 1.9959 | 976 | 0.4698 | 25.2364 |
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- | 0.1966 | 2.9939 | 1464 | 0.3005 | 18.3346 |
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- | 0.1169 | 3.9918 | 1952 | 0.2523 | 16.0413 |
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- | 0.0795 | 4.9898 | 2440 | 0.2257 | 13.6440 |
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- | 0.0525 | 5.9877 | 2928 | 0.2156 | 15.5570 |
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- | 0.0336 | 6.9857 | 3416 | 0.2102 | 15.5905 |
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- | 0.0244 | 7.9836 | 3904 | 0.2036 | 12.6638 |
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- | 0.0182 | 8.9816 | 4392 | 0.1985 | 12.1437 |
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- | 0.012 | 9.9796 | 4880 | 0.1972 | 11.6501 |
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- | 0.0075 | 10.9775 | 5368 | 0.1986 | 12.9840 |
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- | 0.0056 | 11.9755 | 5856 | 0.1959 | 12.5066 |
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- | 0.0043 | 12.9734 | 6344 | 0.1970 | 12.8881 |
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- | 0.0034 | 13.9714 | 6832 | 0.1957 | 12.1622 |
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- | 0.0028 | 14.9693 | 7320 | 0.1971 | 11.5230 |
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- | 0.0024 | 15.9673 | 7808 | 0.1958 | 12.4280 |
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- | 0.0021 | 16.9652 | 8296 | 0.1964 | 12.4812 |
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- | 0.002 | 17.9632 | 8784 | 0.1976 | 12.8650 |
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- | 0.0018 | 18.9611 | 9272 | 0.1968 | 12.0385 |
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- | 0.0017 | 19.9591 | 9760 | 0.1966 | 12.4315 |
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  ### Framework versions
 
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  datasets:
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  - formospeech/hat_asr_aligned
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  model-index:
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+ - name: Whisper Tiny Hakka Simulated Webcam
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  results: []
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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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+ # Whisper Tiny Hakka Simulated Webcam
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the HAT ASR Aligned dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1428
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+ - Cer: 9.1488
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 64
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  - eval_batch_size: 32
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Cer |
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  |:-------------:|:-------:|:----:|:---------------:|:-------:|
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+ | 0.2406 | 0.9980 | 488 | 0.3252 | 23.5719 |
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+ | 0.1309 | 1.9959 | 976 | 0.2390 | 24.1302 |
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+ | 0.0836 | 2.9939 | 1464 | 0.2087 | 16.4008 |
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+ | 0.0431 | 3.9918 | 1952 | 0.1886 | 18.9368 |
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+ | 0.027 | 4.9898 | 2440 | 0.1932 | 12.6823 |
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+ | 0.0173 | 5.9877 | 2928 | 0.1937 | 11.5218 |
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+ | 0.0098 | 6.9857 | 3416 | 0.1835 | 9.9163 |
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+ | 0.0094 | 7.9836 | 3904 | 0.1782 | 13.6325 |
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+ | 0.0057 | 8.9816 | 4392 | 0.1806 | 14.1642 |
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+ | 0.0051 | 9.9796 | 4880 | 0.1627 | 10.9358 |
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+ | 0.0023 | 10.9775 | 5368 | 0.1680 | 9.8724 |
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+ | 0.0025 | 11.9755 | 5856 | 0.1682 | 14.1179 |
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+ | 0.0007 | 12.9734 | 6344 | 0.1537 | 9.5638 |
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+ | 0.0007 | 13.9714 | 6832 | 0.1586 | 9.7637 |
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+ | 0.0003 | 14.9693 | 7320 | 0.1432 | 8.6807 |
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+ | 0.0001 | 15.9673 | 7808 | 0.1463 | 8.6865 |
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+ | 0.0001 | 16.9652 | 8296 | 0.1445 | 8.1883 |
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+ | 0.0001 | 17.9632 | 8784 | 0.1443 | 8.6044 |
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+ | 0.0001 | 18.9611 | 9272 | 0.1427 | 8.9731 |
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+ | 0.0001 | 19.9591 | 9760 | 0.1428 | 9.1488 |
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  ### Framework versions
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