Update README.md

README.md

@@ -1,12 +1,57 @@
 ---
+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-1b-Swedish
-  results: []
+  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: 18.03  # Required. Example: 20.90
+        name: Test WER Without LM   # Optional. Example: Test WER
+        args: 
+        - learning_rate: 7.5e-05
+        - train_batch_size: 32
+        - eval_batch_size: 8
+        - seed: 42
+        - gradient_accumulation_steps: 4
+        - 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: 5.69  # Required. Example: 20.90
+        name: Test CER  Without LM   # Optional. Example: Test WER
+        args: 
+        - learning_rate: 7.5e-05
+        - train_batch_size: 32
+        - eval_batch_size: 8
+        - seed: 42
+        - gradient_accumulation_steps: 4
+        - 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
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,10 +61,16 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset.
 It achieves the following results on the evaluation set:
+
+**Without LM**
 - Loss: 0.3370
 - Wer: 0.1803
 - Cer: 0.0569
 
+**With LM**
+
+
+
 ## Model description
 
 More information needed