Update README.md

README.md

@@ -1,12 +1,58 @@
 ---
+language: 
+- sv-SE
+
 license: apache-2.0
 tags:
-- generated_from_trainer
+- automatic-speech-recognition
+- robust-speech-event
 datasets:
-- common_voice
+- mozilla-foundation/common_voice_8_0
+metrics:
+- wer
+- cer
 model-index:
-- name: wav2vec2-large-xls-r-300m-Swedish
-  results: []
+- name: wav2vec2-xls-r-300m-swedish
+  results:
+  - task: 
+      type: automatic-speech-recognition  # Required. Example: automatic-speech-recognition
+      name: Speech Recognition  # Optional. Example: Speech Recognition
+    dataset:
+      type: mozilla-foundation/common_voice_8_0  # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
+      name: Common Voice sv-SE # Required. Example: Common Voice zh-CN
+      args: sv-SE       # Optional. Example: zh-CN
+    metrics:
+      - type: wer    # Required. Example: wer
+        value: 24.73  # Required. Example: 20.90
+        name: Test WER    # Optional. Example: Test WER
+        args: 
+        - learning_rate: 7.5e-05
+        - train_batch_size: 64
+        - eval_batch_size: 8
+        - seed: 42
+        - gradient_accumulation_steps: 2
+        - total_train_batch_size: 128
+        - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+        - lr_scheduler_type: linear
+        - lr_scheduler_warmup_steps: 1000
+        - num_epochs: 50
+        - mixed_precision_training: Native AMP       # Optional. Example for BLEU: max_order
+      - type: cer    # Required. Example: wer
+        value: 7.58  # Required. Example: 20.90
+        name: Test CER    # Optional. Example: Test WER
+        args: 
+        - learning_rate: 7.5e-05
+        - train_batch_size: 64
+        - eval_batch_size: 8
+        - seed: 42
+        - gradient_accumulation_steps: 2
+        - total_train_batch_size: 128
+        - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+        - lr_scheduler_type: linear
+        - lr_scheduler_warmup_steps: 1000
+        - num_epochs: 50
+        - mixed_precision_training: Native AMP        # Optional. Example for BLEU: max_order
+
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -20,17 +66,6 @@ It achieves the following results on the evaluation set:
 - Wer: 0.2473
 - Cer: 0.0758
 
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
 
 ## Training procedure