Create README.md

README.md

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+---
+language:
+- mr
+license: apache-2.0
+tags:
+- automatic-speech-recognition
+- mozilla-foundation/common_voice_8_0
+- generated_from_trainer
+- robust-speech-event
+datasets:
+- common_voice
+model-index:
+- name: wav2vec2-large-xls-r-300m-mr
+  results:
+  - task: 
+      type: automatic-speech-recognition
+      name: Speech Recognition
+    dataset:
+      type: mozilla-foundation/common_voice_8_0
+      name: Common Voice 8
+      args: mr
+    metrics:
+      - type: wer    # Required. Example: wer
+        value: 31.57  # Required. Example: 20.90
+        name: Test WER    # Optional. Example: Test WER
+      - name: Test CER
+        type: cer
+        value: 6.93
+---
+
+<!-- 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. -->
+
+# 
+
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MR dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.494580
+- Wer: 0.395909
+
+## 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: 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: 1000
+- num_epochs: 200.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+ [12991/14200 9:46:02 < 54:32, 0.37 it/s, Epoch 182.96/200]
+Step	Training Loss	Validation Loss	Wer
+400	3.794000	3.532227	1.000000
+800	3.362400	3.359044	1.000000
+1200	2.293900	1.011279	0.829924
+1600	1.233000	0.502743	0.593662
+2000	0.962600	0.412519	0.496992
+2400	0.831800	0.402903	0.493783
+2800	0.737000	0.389773	0.469314
+3200	0.677100	0.373987	0.436021
+3600	0.634400	0.383823	0.432010
+4000	0.586000	0.375610	0.419575
+4400	0.561000	0.387891	0.418371
+4800	0.518500	0.386357	0.417569
+5200	0.515300	0.415069	0.430004
+5600	0.478100	0.399211	0.408744
+6000	0.468100	0.424542	0.402327
+6400	0.439400	0.430979	0.410750
+6800	0.429600	0.427700	0.409146
+7200	0.400300	0.451111	0.419976
+7600	0.395100	0.463446	0.405134
+8000	0.381800	0.454752	0.407942
+8400	0.371500	0.461547	0.404733
+8800	0.362500	0.461543	0.411151
+9200	0.338200	0.468299	0.417168
+9600	0.338800	0.480989	0.412355
+10000	0.317600	0.475700	0.410750
+10400	0.315100	0.478920	0.403530
+10800	0.296200	0.480600	0.398315
+11200	0.299000	0.477083	0.393502
+11600	0.290000	0.465646	0.393903
+12000	0.290900	0.490041	0.405937
+12400	0.275600	0.489354	0.399519
+12800	0.272600	0.494580	0.395909
+
+
+### Framework versions
+
+- Transformers 4.17.0.dev0
+- Pytorch 1.10.2+cu113
+- Datasets 1.18.3.dev0
+- Tokenizers 0.11.0