update model card README.md

README.md

@@ -8,56 +8,9 @@ tags:
 - collectivat/tv3_parla
 - projecte-aina/parlament_parla
 - generated_from_trainer
-- robust-speech-event
-datasets:
-- mozilla-foundation/common_voice_8_0
-- collectivat/tv3_parla
-- projecte-aina/parlament_parla
 model-index:
 - name: wav2vec2-xls-r-300m-ca
-  results:
-  - task: 
-      name: Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: mozilla-foundation/common_voice_8_0 ca
-      type: mozilla-foundation/common_voice_8_0
-      args: ca
-    metrics:
-       - name: Test WER
-         type: wer
-         value: 0.15636874077301
-       - name: Test CER
-         type: cer
-         value: 0.04086725403909639
-  - task: 
-      name: Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: projecte-aina/parlament_parla ca
-      type: projecte-aina/parlament_parla
-      args: clean
-    metrics:
-       - name: Test WER
-         type: wer
-         value: 0.09940385143350199
-       - name: Test CER
-         type: cer
-         value: 0.026906712890009454
-  - task: 
-      name: Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: collectivat/tv3_parla ca
-      type: collectivat/tv3_parla
-      args: ca
-    metrics:
-       - name: Test WER
-         type: wer
-         value: 0.27349193517342263
-       - name: Test CER
-         type: cer
-         value: 0.11571091827304163
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -67,8 +20,8 @@ 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_8_0 - CA dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2758
-- Wer: 0.1792
+- Loss: 0.2549
+- Wer: 0.1573
 
 ## Model description
 
@@ -96,7 +49,7 @@ 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: 2000
-- num_epochs: 6.0
+- num_epochs: 12.0
 - mixed_precision_training: Native AMP
 
 ### Training results
@@ -125,6 +78,29 @@ The following hyperparameters were used during training:
 | 1.1407        | 5.33  | 10000 | 0.2768          | 0.1798 |
 | 1.1401        | 5.59  | 10500 | 0.2780          | 0.1816 |
 | 1.1333        | 5.86  | 11000 | 0.2748          | 0.1750 |
+| 1.1571        | 6.13  | 11500 | 0.2808          | 0.1708 |
+| 1.1505        | 6.39  | 12000 | 0.2726          | 0.1692 |
+| 1.1519        | 6.66  | 12500 | 0.2749          | 0.1654 |
+| 1.136         | 6.93  | 13000 | 0.2765          | 0.1643 |
+| 1.1326        | 7.19  | 13500 | 0.2706          | 0.1668 |
+| 1.1342        | 7.46  | 14000 | 0.2665          | 0.1638 |
+| 1.1286        | 7.72  | 14500 | 0.2669          | 0.1636 |
+| 1.1243        | 7.99  | 15000 | 0.2619          | 0.1623 |
+| 1.1173        | 8.26  | 15500 | 0.2652          | 0.1604 |
+| 1.1129        | 8.52  | 16000 | 0.2610          | 0.1598 |
+| 1.1091        | 8.79  | 16500 | 0.2608          | 0.1584 |
+| 1.1053        | 9.06  | 17000 | 0.2633          | 0.1664 |
+| 1.1004        | 9.32  | 17500 | 0.2594          | 0.1662 |
+| 1.0995        | 9.59  | 18000 | 0.2623          | 0.1569 |
+| 1.0964        | 9.86  | 18500 | 0.2624          | 0.1597 |
+| 1.09          | 10.12 | 19000 | 0.2577          | 0.1578 |
+| 1.089         | 10.39 | 19500 | 0.2574          | 0.1531 |
+| 1.0864        | 10.66 | 20000 | 0.2556          | 0.1546 |
+| 1.0806        | 10.92 | 20500 | 0.2548          | 0.1583 |
+| 1.0842        | 11.19 | 21000 | 0.2550          | 0.1542 |
+| 1.0805        | 11.45 | 21500 | 0.2561          | 0.1524 |
+| 1.0722        | 11.72 | 22000 | 0.2540          | 0.1566 |
+| 1.0763        | 11.99 | 22500 | 0.2549          | 0.1572 |
 
 
 ### Framework versions