update model card README.md

README.md

@@ -1,73 +1,23 @@
 ---
-language:
-- sv-SE
 license: cc0-1.0
 tags:
-- automatic-speech-recognition
 - generated_from_trainer
-- hf-asr-leaderboard
-- model_for_talk
-- mozilla-foundation/common_voice_8_0
-- robust-speech-event
-- sv
 datasets:
-- mozilla-foundation/common_voice_8_0
+- common_voice
 model-index:
-- name: XLS-R-300M - Swedish
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: mozilla-foundation/common_voice_8_0
-      type: mozilla-foundation/common_voice_8_0
-      args: sv-SE
-    metrics:
-    - name: Test WER
-      type: wer
-      value: 8.72
-    - name: Test CER
-      type: cer
-      value: 3.05
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: speech-recognition-community-v2/eval_data
-      type: speech-recognition-community-v2/eval_data
-      args: sv
-    metrics:
-    - name: Validation WER
-      type: wer
-      value: 19.67
-    - name: Validation CER
-      type: cer
-      value: 8.94
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: speech-recognition-community-v2/eval_data
-      type: speech-recognition-community-v2/eval_data
-      args: sv
-    metrics:
-    - name: Test WER
-      type: wer
-      value: 15.94
-    - name: Test CER
-      type: cer
-      value: 7.71
-widget:
-- example_title: Swedish
-  src: https://cdn-media.huggingface.co/speech_samples/cv_swedish_1.mp3
+- name: ''
+  results: []
 ---
 
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
 # 
 
-This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SV-SE dataset.
+This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the common_voice dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1595
-- Wer: 0.1200
+- Loss: 0.1321
+- Wer: 0.1115
 
 ## Model description
 
@@ -86,7 +36,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.00025
+- learning_rate: 7.5e-05
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
@@ -94,7 +44,7 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 128
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.25
+- lr_scheduler_warmup_ratio: 0.2
 - num_epochs: 100.0
 - mixed_precision_training: Native AMP
 
@@ -102,29 +52,20 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 3.0418        | 5.49  | 500  | 3.0176          | 1.0    |
-| 1.1819        | 10.98 | 1000 | 0.2562          | 0.2168 |
-| 1.0032        | 16.48 | 1500 | 0.1746          | 0.1546 |
-| 0.9077        | 21.97 | 2000 | 0.1600          | 0.1339 |
-| 0.8687        | 27.47 | 2500 | 0.1647          | 0.1378 |
-| 0.8081        | 32.96 | 3000 | 0.1608          | 0.1353 |
-| 0.7923        | 38.46 | 3500 | 0.1534          | 0.1277 |
-| 0.7349        | 43.95 | 4000 | 0.1546          | 0.1303 |
-| 0.7199        | 49.45 | 4500 | 0.1617          | 0.1277 |
-| 0.7028        | 54.94 | 5000 | 0.1572          | 0.1287 |
-| 0.6912        | 60.44 | 5500 | 0.1560          | 0.1249 |
-| 0.6492        | 65.93 | 6000 | 0.1542          | 0.1260 |
-| 0.6407        | 71.43 | 6500 | 0.1605          | 0.1240 |
-| 0.6222        | 76.92 | 7000 | 0.1577          | 0.1219 |
-| 0.6039        | 82.42 | 7500 | 0.1645          | 0.1249 |
-| 0.5928        | 87.91 | 8000 | 0.1590          | 0.1214 |
-| 0.6022        | 93.4  | 8500 | 0.1597          | 0.1213 |
-| 0.5814        | 98.9  | 9000 | 0.1599          | 0.1199 |
+| 2.9099        | 10.42 | 1000 | 2.8369          | 1.0    |
+| 1.0745        | 20.83 | 2000 | 0.1957          | 0.1673 |
+| 0.934         | 31.25 | 3000 | 0.1579          | 0.1389 |
+| 0.8691        | 41.66 | 4000 | 0.1457          | 0.1290 |
+| 0.8328        | 52.08 | 5000 | 0.1435          | 0.1205 |
+| 0.8068        | 62.5  | 6000 | 0.1350          | 0.1191 |
+| 0.7822        | 72.91 | 7000 | 0.1347          | 0.1155 |
+| 0.7769        | 83.33 | 8000 | 0.1321          | 0.1131 |
+| 0.7678        | 93.75 | 9000 | 0.1321          | 0.1115 |
 
 
 ### Framework versions
 
 - Transformers 4.17.0.dev0
 - Pytorch 1.10.2+cu102
-- Datasets 1.18.3
+- Datasets 2.2.2
 - Tokenizers 0.11.0