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Segementation

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README.md CHANGED
@@ -21,8 +21,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0037
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- - Wer: 0.0571
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- - Cer: 0.0223
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  ## Model description
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@@ -57,31 +57,31 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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  |:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
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- | 0.0078 | 1.0 | 282 | 0.0037 | 0.0529 | 0.0209 |
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- | 0.0047 | 2.0 | 564 | 0.0040 | 0.0550 | 0.0208 |
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- | 0.0018 | 3.0 | 846 | 0.0050 | 0.0646 | 0.0261 |
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- | 0.0013 | 4.0 | 1128 | 0.0053 | 0.0594 | 0.0224 |
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- | 0.0009 | 5.0 | 1410 | 0.0062 | 0.0659 | 0.0241 |
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- | 0.0008 | 6.0 | 1692 | 0.0066 | 0.0659 | 0.0257 |
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- | 0.0008 | 7.0 | 1974 | 0.0068 | 0.0626 | 0.0243 |
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- | 0.0006 | 8.0 | 2256 | 0.0072 | 0.0615 | 0.0223 |
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- | 0.0006 | 9.0 | 2538 | 0.0075 | 0.0668 | 0.0256 |
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- | 0.0003 | 10.0 | 2820 | 0.0077 | 0.0643 | 0.0238 |
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- | 0.0003 | 11.0 | 3102 | 0.0082 | 0.0577 | 0.0211 |
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- | 0.0002 | 12.0 | 3384 | 0.0090 | 0.0643 | 0.0237 |
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- | 0.0002 | 13.0 | 3666 | 0.0100 | 0.0637 | 0.0222 |
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- | 0.0001 | 14.0 | 3948 | 0.0100 | 0.0615 | 0.0229 |
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- | 0.0001 | 15.0 | 4230 | 0.0104 | 0.0603 | 0.0232 |
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- | 0.0001 | 16.0 | 4512 | 0.0111 | 0.0606 | 0.0216 |
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- | 0.0001 | 17.0 | 4794 | 0.0115 | 0.0614 | 0.0211 |
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- | 0.0 | 18.0 | 5076 | 0.0115 | 0.0570 | 0.0196 |
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- | 0.0 | 19.0 | 5358 | 0.0121 | 0.0614 | 0.0225 |
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- | 0.0 | 20.0 | 5640 | 0.0119 | 0.0595 | 0.0219 |
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- | 0.0 | 21.0 | 5922 | 0.0121 | 0.0588 | 0.0209 |
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- | 0.0 | 22.0 | 6204 | 0.0121 | 0.0597 | 0.0215 |
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- | 0.0 | 23.0 | 6486 | 0.0121 | 0.0601 | 0.0215 |
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- | 0.0 | 24.0 | 6768 | 0.0126 | 0.0609 | 0.0234 |
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- | 0.0 | 24.9130 | 7025 | 0.0121 | 0.0588 | 0.0204 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0037
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+ - Wer: 0.0528
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+ - Cer: 0.0213
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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  |:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
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+ | 0.0061 | 1.0 | 282 | 0.0036 | 0.0474 | 0.0188 |
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+ | 0.0039 | 2.0 | 564 | 0.0040 | 0.0552 | 0.0217 |
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+ | 0.0021 | 3.0 | 846 | 0.0047 | 0.0563 | 0.0222 |
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+ | 0.0011 | 4.0 | 1128 | 0.0055 | 0.0579 | 0.0200 |
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+ | 0.0008 | 5.0 | 1410 | 0.0058 | 0.0579 | 0.0225 |
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+ | 0.0007 | 6.0 | 1692 | 0.0061 | 0.0572 | 0.0194 |
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+ | 0.0006 | 7.0 | 1974 | 0.0063 | 0.0576 | 0.0208 |
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+ | 0.0005 | 8.0 | 2256 | 0.0063 | 0.0664 | 0.0246 |
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+ | 0.0003 | 9.0 | 2538 | 0.0077 | 0.0715 | 0.0254 |
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+ | 0.0003 | 10.0 | 2820 | 0.0074 | 0.0666 | 0.0256 |
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+ | 0.0004 | 11.0 | 3102 | 0.0075 | 0.0626 | 0.0244 |
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+ | 0.0001 | 12.0 | 3384 | 0.0083 | 0.0617 | 0.0234 |
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+ | 0.0002 | 13.0 | 3666 | 0.0083 | 0.0655 | 0.0228 |
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+ | 0.0001 | 14.0 | 3948 | 0.0100 | 0.0617 | 0.0219 |
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+ | 0.0001 | 15.0 | 4230 | 0.0109 | 0.0648 | 0.0224 |
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+ | 0.0001 | 16.0 | 4512 | 0.0113 | 0.0610 | 0.0196 |
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+ | 0.0 | 17.0 | 4794 | 0.0120 | 0.0612 | 0.0212 |
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+ | 0.0001 | 18.0 | 5076 | 0.0127 | 0.0601 | 0.0220 |
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+ | 0.0 | 19.0 | 5358 | 0.0134 | 0.0581 | 0.0208 |
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+ | 0.0 | 20.0 | 5640 | 0.0135 | 0.0597 | 0.0226 |
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+ | 0.0 | 21.0 | 5922 | 0.0134 | 0.0570 | 0.0205 |
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+ | 0.0 | 22.0 | 6204 | 0.0133 | 0.0579 | 0.0209 |
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+ | 0.0 | 23.0 | 6486 | 0.0133 | 0.0577 | 0.0208 |
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+ | 0.0 | 24.0 | 6768 | 0.0138 | 0.0605 | 0.0236 |
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+ | 0.0 | 24.9130 | 7025 | 0.0134 | 0.0583 | 0.0205 |
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  ### Framework versions
generation_config.json CHANGED
@@ -40,16 +40,7 @@
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  "bos_token_id": 50257,
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  "decoder_start_token_id": 50258,
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  "eos_token_id": 50257,
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  "is_multilingual": true,
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  "lang_to_id": {
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  "<|af|>": 50327,
 
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  "bos_token_id": 50257,
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  "decoder_start_token_id": 50258,
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  "eos_token_id": 50257,
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  "is_multilingual": true,
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