chmanoj
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xls-r-1B-te

Automatic Speech Recognition

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robust-speech-event

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chmanoj commited on Jan 28, 2022

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update model card README.md

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@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the OPENSLR_SLR66 - NA dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5929
-- Wer: 0.7180
 ## Model description
@@ -37,7 +37,7 @@ More information needed
 ### Training hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
 - train_batch_size: 16
 - eval_batch_size: 4
 - seed: 42
@@ -53,16 +53,16 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 1.5794        | 9.61  | 500  | 0.9860          | 0.9582 |
-| 1.0985        | 19.23 | 1000 | 0.5948          | 0.7534 |
-| 0.9551        | 28.84 | 1500 | 0.5892          | 0.7392 |
-| 0.8699        | 38.46 | 2000 | 0.5927          | 0.72   |
-| 0.8372        | 48.08 | 2500 | 0.5939          | 0.7385 |
-| 0.7794        | 57.69 | 3000 | 0.5801          | 0.7388 |
-| 0.7565        | 67.31 | 3500 | 0.5827          | 0.7184 |
-| 0.7303        | 76.92 | 4000 | 0.5800          | 0.7297 |
-| 0.7128        | 86.54 | 4500 | 0.5977          | 0.7150 |
-| 0.6972        | 96.15 | 5000 | 0.5901          | 0.7177 |
 ### Framework versions

 This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the OPENSLR_SLR66 - NA dataset.
 It achieves the following results on the evaluation set:
+- Loss: 3.3845
+- Wer: 0.9869
 ## Model description
 ### Training hyperparameters
 The following hyperparameters were used during training:
+- learning_rate: 5e-07
 - train_batch_size: 16
 - eval_batch_size: 4
 - seed: 42
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
+| 3.5131        | 9.61  | 500  | 3.5294          | 1.0    |
+| 2.8596        | 19.23 | 1000 | 3.5708          | 1.0    |
+| 1.9055        | 28.84 | 1500 | 3.6433          | 1.0007 |
+| 1.4239        | 38.46 | 2000 | 3.6569          | 0.9995 |
+| 1.2168        | 48.08 | 2500 | 3.6079          | 0.9957 |
+| 1.1063        | 57.69 | 3000 | 3.5738          | 0.9925 |
+| 1.0404        | 67.31 | 3500 | 3.4857          | 0.9889 |
+| 1.001         | 76.92 | 4000 | 3.4882          | 0.9858 |
+| 0.982         | 86.54 | 4500 | 3.3851          | 0.9871 |
+| 0.9612        | 96.15 | 5000 | 3.3869          | 0.9873 |
 ### Framework versions