kapilkd13
/

xls-r-hi-test

@@ -21,8 +21,8 @@ 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 MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - HI dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7122
-- Wer: 1.0107
 ## Model description
@@ -48,23 +48,63 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 200
-- training_steps: 1000
 - mixed_precision_training: Native AMP
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| No log        | 0.34  | 100  | 4.2619          | 0.9999 |
-| No log        | 0.68  | 200  | 3.3447          | 1.0    |
-| No log        | 1.02  | 300  | 2.0648          | 1.0031 |
-| No log        | 1.36  | 400  | 1.2481          | 1.0047 |
-| 3.7472        | 1.69  | 500  | 1.0773          | 1.0110 |
-| 3.7472        | 2.03  | 600  | 0.9298          | 1.0174 |
-| 3.7472        | 2.37  | 700  | 0.8264          | 1.0098 |
-| 3.7472        | 2.71  | 800  | 0.7596          | 1.0075 |
-| 3.7472        | 3.05  | 900  | 0.7256          | 1.0066 |
-| 0.4913        | 3.39  | 1000 | 0.7122          | 1.0107 |
 ### 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 MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - HI dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.9201
+- Wer: 1.0091
 ## Model description
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 200
+- training_steps: 5000
 - mixed_precision_training: Native AMP
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
+| No log        | 0.34  | 100  | 4.2570          | 0.9999 |
+| No log        | 0.68  | 200  | 3.3222          | 1.0005 |
+| No log        | 1.02  | 300  | 2.3755          | 1.0    |
+| No log        | 1.36  | 400  | 1.4071          | 1.0037 |
+| 3.8379        | 1.69  | 500  | 1.2223          | 1.0091 |
+| 3.8379        | 2.03  | 600  | 1.0885          | 1.0273 |
+| 3.8379        | 2.37  | 700  | 0.9818          | 1.0098 |
+| 3.8379        | 2.71  | 800  | 0.9154          | 1.0110 |
+| 3.8379        | 3.05  | 900  | 0.8869          | 1.0154 |
+| 0.5888        | 3.39  | 1000 | 0.8976          | 1.0149 |
+| 0.5888        | 3.73  | 1100 | 0.8323          | 1.0124 |
+| 0.5888        | 4.07  | 1200 | 0.8488          | 1.0087 |
+| 0.5888        | 4.41  | 1300 | 0.8659          | 1.0069 |
+| 0.5888        | 4.75  | 1400 | 0.8612          | 1.0043 |
+| 0.3706        | 5.08  | 1500 | 0.8300          | 1.0183 |
+| 0.3706        | 5.42  | 1600 | 0.8417          | 1.0091 |
+| 0.3706        | 5.76  | 1700 | 0.8261          | 1.0087 |
+| 0.3706        | 6.1   | 1800 | 0.8548          | 1.0068 |
+| 0.3706        | 6.44  | 1900 | 0.7984          | 1.0110 |
+| 0.2671        | 6.78  | 2000 | 0.8388          | 1.0117 |
+| 0.2671        | 7.12  | 2100 | 0.8499          | 1.0073 |
+| 0.2671        | 7.46  | 2200 | 0.8480          | 1.0112 |
+| 0.2671        | 7.8   | 2300 | 0.7929          | 1.0099 |
+| 0.2671        | 8.14  | 2400 | 0.8659          | 1.0089 |
+| 0.2017        | 8.47  | 2500 | 0.8583          | 1.0063 |
+| 0.2017        | 8.81  | 2600 | 0.8326          | 1.0110 |
+| 0.2017        | 9.15  | 2700 | 0.8759          | 1.0037 |
+| 0.2017        | 9.49  | 2800 | 0.8576          | 1.0100 |
+| 0.2017        | 9.83  | 2900 | 0.8777          | 1.0224 |
+| 0.1682        | 10.17 | 3000 | 0.8865          | 1.0280 |
+| 0.1682        | 10.51 | 3100 | 0.9213          | 1.0068 |
+| 0.1682        | 10.85 | 3200 | 0.8881          | 1.0152 |
+| 0.1682        | 11.19 | 3300 | 0.9089          | 1.0100 |
+| 0.1682        | 11.53 | 3400 | 0.8974          | 1.0127 |
+| 0.1347        | 11.86 | 3500 | 0.9129          | 1.0123 |
+| 0.1347        | 12.2  | 3600 | 0.9939          | 1.0169 |
+| 0.1347        | 12.54 | 3700 | 0.9135          | 1.0083 |
+| 0.1347        | 12.88 | 3800 | 0.9229          | 1.0118 |
+| 0.1347        | 13.22 | 3900 | 0.9610          | 1.0107 |
+| 0.1049        | 13.56 | 4000 | 0.9236          | 1.0099 |
+| 0.1049        | 13.9  | 4100 | 0.8967          | 1.0085 |
+| 0.1049        | 14.24 | 4200 | 0.8980          | 1.0081 |
+| 0.1049        | 14.58 | 4300 | 0.9023          | 1.0081 |
+| 0.1049        | 14.92 | 4400 | 0.9216          | 1.0079 |
+| 0.0917        | 15.25 | 4500 | 0.9443          | 1.0090 |
+| 0.0917        | 15.59 | 4600 | 0.9390          | 1.0091 |
+| 0.0917        | 15.93 | 4700 | 0.9153          | 1.0083 |
+| 0.0917        | 16.27 | 4800 | 0.9190          | 1.0092 |
+| 0.0917        | 16.61 | 4900 | 0.9194          | 1.0091 |
+| 0.0786        | 16.95 | 5000 | 0.9201          | 1.0091 |
 ### Framework versions