Create README.md

README.md

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+---
+language: et
+datasets:
+- mozilla-foundation/common_voice_8_0
+metrics:
+- wer
+- cer
+tags:
+- generated_from_trainer
+- mozilla-foundation/common_voice_8_0
+- audio
+- automatic-speech-recognition
+- speech
+- robust-speech-event
+model-index:
+- name: XLS-R 1B Wav2Vec2 Estonian by Rasmus Toivanen
+  results:
+  - task: 
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 8
+      type: mozilla-foundation/common_voice_8_0
+      args: et
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 20.12
+       - name: Test CER
+         type: cer
+         value: 3.82
+---
+<!-- 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-et-lm-1B
+
+This model was finetuned with mozilla_foundation/common_voice_8_0 et with train+other+validation splits.
+It achieves the following results on the test set:
+(Loss reported with last eval step at step 2000/2040 during training)
+- Loss: 0.2150 
+- Wer: 0.2012
+
+## 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: 0.00005
+- train_batch_size: 32
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 1
+- 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: 500
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+
+
+
+### Framework versions
+
+- Transformers 4.17.0.dev0
+- Pytorch 1.10.2+cu102
+- Datasets 1.18.3
+- Tokenizers 0.11.0