Create README.md

README.md

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+---
+tags:
+- automatic-speech-recognition
+- librispeech_asr
+- generated_from_trainer
+model-index:
+- name: wav2vec2-2-bart-base
+  results: []
+---
+
+<!-- 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. -->
+
+# wav2vec2-2-bart-base
+
+This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) and [bart-base](https://huggingface.co/facebook/bart-base) on the librispeech_asr - clean dataset.
+  
+It achieves the following results on the evaluation set:
+- Loss: 0.405
+- Wer: 0.0728
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 64
+- total_eval_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 400
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+See Training Metrics Tab.
+
+
+### Framework versions
+
+- Transformers 4.15.0.dev0
+- Pytorch 1.9.0+cu111
+- Datasets 1.16.2.dev0
+- Tokenizers 0.10.3