AiLab-IMCS-UL
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whisper-large-v3-lv-late-cv17

Automatic Speech Recognition

Inference Endpoints

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normundsg commited on May 23

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@@ -17,8 +17,7 @@ We also provide 4-bit, 5-bit and 8-bit quantized versions of the model in the GG
 Fine-tuning was done using the Hugging Face Transformers library with a modified [seq2seq script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/speech-recognition#sequence-to-sequence).
-Training data:
-| Dataset | Hours |
 |:---|---:|
 | Latvian CV 17.0 train set (the [V1 split](https://analyzer.cv-toolbox.web.tr/examine/lv/17.0)) | 167 |
 | LATE-Media train set | 42 |
@@ -28,7 +27,7 @@ Training data:
 The model is evaluated on both a Latvian CV 17.0 test set (the [V1 split](https://analyzer.cv-toolbox.web.tr/examine/lv/17.0)) and a [LATE-Media test set](http://hdl.handle.net/20.500.12574/99).
-| Dataset | WER | CER |
 |:---|---:|---:|
 | Latvian CV 17.0 V1 - formatted | 5.0 | 1.6 |
 | Latvian CV 17.0 V1 - normalized | 3.4 | 1.0 |

 Fine-tuning was done using the Hugging Face Transformers library with a modified [seq2seq script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/speech-recognition#sequence-to-sequence).
+| Training data | Hours |
 |:---|---:|
 | Latvian CV 17.0 train set (the [V1 split](https://analyzer.cv-toolbox.web.tr/examine/lv/17.0)) | 167 |
 | LATE-Media train set | 42 |
 The model is evaluated on both a Latvian CV 17.0 test set (the [V1 split](https://analyzer.cv-toolbox.web.tr/examine/lv/17.0)) and a [LATE-Media test set](http://hdl.handle.net/20.500.12574/99).
+| Testing data | WER | CER |
 |:---|---:|---:|
 | Latvian CV 17.0 V1 - formatted | 5.0 | 1.6 |
 | Latvian CV 17.0 V1 - normalized | 3.4 | 1.0 |