henilp105
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wav2vec2-large-xls-r-300m-telugu-asr

Automatic Speech Recognition

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henil panchal commited on Dec 23, 2022

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update model card README.md

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@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [henilp105/wav2vec2-large-xls-r-300m-telugu-asr](https://huggingface.co/henilp105/wav2vec2-large-xls-r-300m-telugu-asr) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.3902
-- Wer: 0.7443
 ## Model description
@@ -52,19 +52,19 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 6.9225        | 2.3   | 200  | 3.3972          | 1.0    |
-| 1.4526        | 4.59  | 400  | 1.0196          | 0.7959 |
-| 0.5384        | 6.89  | 600  | 1.0260          | 0.7790 |
-| 0.3483        | 9.19  | 800  | 1.0932          | 0.7740 |
-| 0.2428        | 11.49 | 1000 | 1.2085          | 0.7747 |
-| 0.1839        | 13.79 | 1200 | 1.2716          | 0.7750 |
-| 0.147         | 16.09 | 1400 | 1.2895          | 0.7665 |
-| 0.1238        | 18.39 | 1600 | 1.2995          | 0.7585 |
-| 0.1046        | 20.69 | 1800 | 1.3891          | 0.7550 |
-| 0.0946        | 22.98 | 2000 | 1.3820          | 0.7603 |
-| 0.0856        | 25.29 | 2200 | 1.3909          | 0.7438 |
-| 0.0753        | 27.58 | 2400 | 1.3841          | 0.7431 |
-| 0.075         | 29.88 | 2600 | 1.3902          | 0.7443 |
 ### Framework versions

 This model is a fine-tuned version of [henilp105/wav2vec2-large-xls-r-300m-telugu-asr](https://huggingface.co/henilp105/wav2vec2-large-xls-r-300m-telugu-asr) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 1.2528
+- Wer: 0.7044
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
+| 6.2329        | 2.3   | 200  | 1.0480          | 0.7942 |
+| 0.7353        | 4.59  | 400  | 0.8799          | 0.7307 |
+| 0.4454        | 6.89  | 600  | 0.9360          | 0.7384 |
+| 0.3191        | 9.19  | 800  | 0.9886          | 0.7312 |
+| 0.2246        | 11.49 | 1000 | 1.1062          | 0.7396 |
+| 0.1796        | 13.79 | 1200 | 1.1293          | 0.7250 |
+| 0.1454        | 16.09 | 1400 | 1.1771          | 0.7287 |
+| 0.121         | 18.39 | 1600 | 1.1947          | 0.7173 |
+| 0.1046        | 20.69 | 1800 | 1.2373          | 0.7277 |
+| 0.0903        | 22.98 | 2000 | 1.2815          | 0.7193 |
+| 0.0811        | 25.29 | 2200 | 1.2602          | 0.7148 |
+| 0.0722        | 27.58 | 2400 | 1.2517          | 0.7121 |
+| 0.0673        | 29.88 | 2600 | 1.2528          | 0.7044 |
 ### Framework versions