Update README.md

README.md

@@ -1,96 +1,31 @@
---- 
-language: 
+---
+language:
 - fi
 lisence: apache-2.0
-tags: 
+tags:
 - automatic-speech-recognition
 - mozilla-foundation/common_voice_7_0
 - generated_from_trainer
 - fi
 - speech
 - robust-speech-event
-datasets: 
+datasets:
 - mozilla-foundation/common_voice_7_0
-model-index: 
+model-index:
 - name: XLS-R 1B Wav2Vec2 Finnish by Rasmus Toivanen
-  results: 
+  results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
-    dataset: 
+    dataset:
       name: Common Voice 7
       type: mozilla-foundation/common_voice_7_0
       args: fi
-    metrics: 
+    metrics:
       - name: Test WER
         type: wer
         value: 10.96
       - name: Test CER
         type: cer
         value: 2.81
----
-
-<!-- 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. -->
-
-# wav2vec2-xlsr-fi-train-aug-lm-1B
-
-This model was trained from scratch on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1499
-- Wer: 0.1955
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 8
-- eval_batch_size: 8
-- seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 16
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 100
-- num_epochs: 4
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Wer    |
-|:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.6473        | 0.29  | 400  | 0.2857          | 0.3825 |
-| 0.6039        | 0.58  | 800  | 0.2459          | 0.3476 |
-| 0.4757        | 0.87  | 1200 | 0.2338          | 0.3274 |
-| 0.4473        | 1.15  | 1600 | 0.2246          | 0.3128 |
-| 0.4322        | 1.44  | 2000 | 0.1962          | 0.2805 |
-| 0.3961        | 1.73  | 2400 | 0.2070          | 0.2797 |
-| 0.3642        | 2.02  | 2800 | 0.1790          | 0.2473 |
-| 0.3561        | 2.31  | 3200 | 0.1769          | 0.2375 |
-| 0.282         | 2.6   | 3600 | 0.1672          | 0.2263 |
-| 0.2978        | 2.89  | 4000 | 0.1636          | 0.2192 |
-| 0.2722        | 3.17  | 4400 | 0.1637          | 0.2102 |
-| 0.2924        | 3.46  | 4800 | 0.1506          | 0.2021 |
-| 0.2631        | 3.75  | 5200 | 0.1499          | 0.1955 |
-
-
-### Framework versions
-
-- Transformers 4.16.0.dev0
-- Pytorch 1.10.1+cu102
-- Datasets 1.17.1.dev0
-- Tokenizers 0.11.0
+---