Create README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- audiofolder
+metrics:
+- wer
+model-index:
+- name: wav2vec2-xls-r-300m-fleurs_zu-run1
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: audiofolder
+      type: audiofolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.600381
+---
+
+<!-- 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-xls-r-300m-asr_af-run1-fleurs_zu-run1
+
+This model is a fine-tuned version of [lucas-meyer/wav2vec2-xls-r-300m-asr_af-run1](https://huggingface.co/lucas-meyer/wav2vec2-xls-r-300m-asr_af-run1) on the audiofolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.578752
+- Wer: 0.600381
+
+## 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: 0.0003
+- train_batch_size: 4
+- eval_batch_size: 4
+- 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: 500
+- num_epochs: 30
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 50 | 19.607200 | 9.162900 | 1.000000 |
+| 100 | 7.038300 | 4.738822 | 1.000000 |
+| 150 | 4.190100 | 3.359574 | 1.000000 |
+| 200 | 3.161900 | 3.032595 | 1.000000 |
+| 250 | 3.004700 | 2.994741 | 1.000000 |
+| 300 | 2.988300 | 2.955285 | 1.000000 |
+| 350 | 2.675800 | 1.816109 | 1.000000 |
+| 400 | 1.064400 | 0.866473 | 0.814220 |
+| 450 | 0.601600 | 0.696754 | 0.712340 |
+| 500 | 0.506900 | 0.662974 | 0.716426 |
+| 550 | 0.432200 | 0.598446 | 0.667121 |
+| 600 | 0.358700 | 0.618853 | 0.681013 |
+| 650 | 0.333300 | 0.564290 | 0.627349 |
+| 700 | 0.283100 | 0.573746 | 0.646418 |
+| 750 | 0.250800 | 0.577737 | 0.639608 |
+| 800 | 0.232200 | 0.557288 | 0.604467 |
+| 850 | 0.191200 | 0.538959 | 0.590030 |
+| 900 | 0.195600 | 0.549700 | 0.600654 |
+| 950 | 0.193000 | 0.579098 | 0.611278 |
+| 1000 | 0.169900 | 0.578752 | 0.600381 |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3