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apac_5sents_XLS-R_5e-5

Automatic Speech Recognition

Generated from Trainer

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slplab commited on Dec 1, 2023

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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 [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 110.0941
-- Wer: 1.0
 ## Model description
@@ -50,14 +50,28 @@ The following hyperparameters were used during training:
 ### Training results
-| Training Loss | Epoch | Step | Validation Loss | Wer |
-|:-------------:|:-----:|:----:|:---------------:|:---:|
-| 234.3396      | 11.11 | 200  | 109.8983        | 1.0 |
-| 77.2486       | 22.22 | 400  | 57.9166         | 1.0 |
-| 45.7285       | 33.32 | 600  | 30.9371         | 1.0 |
-| 20.3966       | 44.43 | 800  | 10.8806         | 1.0 |
-| 7.2844        | 55.54 | 1000 | 5.2260          | 1.0 |
-| 5.0262        | 66.65 | 1200 | 4.7277          | 1.0 |
 ### Framework versions

 This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 1.6693
+- Wer: 0.6607
 ## Model description
 ### Training results
+| Training Loss | Epoch  | Step | Validation Loss | Wer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|
+| 98.1859       | 11.11  | 200  | 75.6610         | 1.0    |
+| 66.0186       | 22.22  | 400  | 52.7194         | 1.0    |
+| 40.6772       | 33.32  | 600  | 26.2206         | 1.0    |
+| 16.4279       | 44.43  | 800  | 8.3596          | 1.0    |
+| 6.1402        | 55.54  | 1000 | 5.3091          | 1.0    |
+| 4.733         | 66.65  | 1200 | 4.5618          | 1.0    |
+| 3.4737        | 77.76  | 1400 | 3.4971          | 1.0    |
+| 1.6412        | 88.86  | 1600 | 2.7199          | 0.9219 |
+| 0.8524        | 99.97  | 1800 | 2.0043          | 0.9241 |
+| 0.6227        | 111.11 | 2000 | 2.1371          | 0.9330 |
+| 0.4834        | 122.22 | 2200 | 1.6094          | 0.9196 |
+| 0.3944        | 133.32 | 2400 | 2.2378          | 0.9531 |
+| 0.2975        | 144.43 | 2600 | 1.7241          | 0.8862 |
+| 0.194         | 155.54 | 2800 | 1.8496          | 0.7679 |
+| 0.1211        | 166.65 | 3000 | 1.4915          | 0.6808 |
+| 0.0866        | 177.76 | 3200 | 1.9463          | 0.6429 |
+| 0.0696        | 188.86 | 3400 | 2.0191          | 0.5737 |
+| 0.0563        | 199.97 | 3600 | 2.4305          | 0.6562 |
+| 0.0461        | 211.11 | 3800 | 1.6485          | 0.6138 |
+| 0.0413        | 222.22 | 4000 | 2.2569          | 0.6272 |
 ### Framework versions