MelanieKoe
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w2v2-base-pretrained_lr1e-4_at0.9_da1

Automatic Speech Recognition

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MelanieKoe commited on Mar 22

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README.md +13 -13
model.safetensors +1 -1

README.md CHANGED Viewed

@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 16.9074
-- Wer: 1.0
 ## Model description
@@ -49,17 +49,17 @@ The following hyperparameters were used during training:
 ### Training results
-| Training Loss | Epoch | Step | Validation Loss | Wer |
-|:-------------:|:-----:|:----:|:---------------:|:---:|
-| 25.5111       | 6.1   | 250  | 21.0169         | 1.0 |
-| 8.8611        | 12.2  | 500  | 18.3862         | 1.0 |
-| 8.2182        | 18.29 | 750  | 16.3061         | 1.0 |
-| 8.1364        | 24.39 | 1000 | 15.6357         | 1.0 |
-| 8.1315        | 30.49 | 1250 | 17.5602         | 1.0 |
-| 8.1532        | 36.59 | 1500 | 16.3879         | 1.0 |
-| 8.0249        | 42.68 | 1750 | 17.4829         | 1.0 |
-| 8.0482        | 48.78 | 2000 | 16.9106         | 1.0 |
-| 8.0999        | 54.88 | 2250 | 16.9074         | 1.0 |
 ### Framework versions

 This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 6.9410
+- Wer: 1.0571
 ## Model description
 ### Training results
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 17.8057       | 6.1   | 250  | 4.5611          | 1.0    |
+| 3.2734        | 12.2  | 500  | 3.7357          | 1.0    |
+| 2.8657        | 18.29 | 750  | 2.7315          | 1.0    |
+| 0.3941        | 24.39 | 1000 | 4.7924          | 1.0529 |
+| 0.1195        | 30.49 | 1250 | 5.4586          | 1.0507 |
+| 0.0721        | 36.59 | 1500 | 6.5058          | 1.0588 |
+| 0.0472        | 42.68 | 1750 | 6.8300          | 1.0614 |
+| 0.0308        | 48.78 | 2000 | 6.8007          | 1.0597 |
+| 0.0247        | 54.88 | 2250 | 6.9410          | 1.0571 |
 ### Framework versions

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