update model card README.md

README.md

@@ -1,3 +1,78 @@
 ---
 license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- common_voice
+metrics:
+- wer
+model-index:
+- name: wav2vec2-large-xls-r-300m-odia-colab
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice
+      type: common_voice
+      config: or
+      split: train+validation
+      args: or
+    metrics:
+    - name: Wer
+      type: wer
+      value: 1.08812729498164
 ---
+
+<!-- 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-large-xls-r-300m-odia-colab
+
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9082
+- Wer: 1.0881
+
+## 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: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- 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    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 5.6443        | 24.97 | 400  | 0.9082          | 1.0881 |
+
+
+### Framework versions
+
+- Transformers 4.24.0
+- Pytorch 1.10.0+cu113
+- Datasets 1.18.3
+- Tokenizers 0.13.2