Create README.md

README.md

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+---
+language:
+- ha
+license: apache-2.0
+tags:
+- automatic-speech-recognition
+- mozilla-foundation/common_voice_8_0
+- generated_from_trainer
+- ha
+- robust-speech-event
+- model_for_talk
+datasets:
+- mozilla-foundation/common_voice_8_0
+
+model-index:
+- name: Akashpb13/Hausa_xlsr
+  results:
+  - task: 
+      name: Automatic Speech Recognition 
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 8
+      type: mozilla-foundation/common_voice_8_0
+      args: kmr
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 0.21177149451817656
+       - name: Test CER
+         type: cer
+         value: 0.04472733528298641
+  - task: 
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Robust Speech Event - Dev Data
+      type: speech-recognition-community-v2/dev_data
+      args: kmr
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 0.21177149451817656
+       - name: Test CER
+         type: cer
+         value: 0.04472733528298641
+---
+
+# Akashpb13/xlsr_hungarian_new
+
+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_7_0 - hu dataset.
+It achieves the following results on the evaluation set (which is 10 percent of train data set merged with invalidated data, reported, other, and dev datasets):
+- Loss: 0.275118
+- Wer: 0.329955
+## Model description
+"facebook/wav2vec2-xls-r-300m" was finetuned.
+
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+Training data - 
+Common voice Hausa train.tsv, dev.tsv, invalidated.tsv, reported.tsv, other.tsv and validated.tsv
+Only those points were considered where upvotes were greater than downvotes and duplicates were removed after concatenation of all the datasets given in common voice 7.0
+
+## Training procedure
+For creating the training dataset, all possible datasets were appended and 90-10 split was used. 
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+
+- learning_rate: 0.000096
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 13
+- gradient_accumulation_steps: 2
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 50
+- mixed_precision_training: Native AMP
+
+
+### Training results
+
+| Step | Training Loss | Validation Loss | Wer      |
+|------|---------------|-----------------|----------|
+| 500  | 5.176500      | 2.776366        | 1.000000 |
+| 1000 | 1.166500      | 0.329668        | 0.482262 |
+| 1500 | 0.334500      | 0.245564        | 0.391304 |
+| 2000 | 0.226300      | 0.241998        | 0.381168 |
+| 2500 | 0.174600      | 0.227778        | 0.356895 |
+| 3000 | 0.141700      | 0.237551        | 0.343292 |
+| 3500 | 0.117600      | 0.259884        | 0.348626 |
+| 4000 | 0.097800      | 0.261468        | 0.343825 |
+| 4500 | 0.083500      | 0.268763        | 0.332889 |
+| 5000 | 0.074500      | 0.276381        | 0.332622 |
+| 5500 | 0.067700      | 0.275504        | 0.328354 |
+| 6000 | 0.064500      | 0.274393        | 0.331288 |
+| 6500 | 0.061400      | 0.275118        | 0.329955 |
+	
+
+
+### Framework versions
+- Transformers 4.16.0.dev0
+- Pytorch 1.10.0+cu102
+- Datasets 1.17.1.dev0
+- Tokenizers 0.10.3
+
+#### Evaluation Commands
+
+1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
+
+```bash
+python eval.py --model_id Akashpb13/Hausa_xlsr --dataset mozilla-foundation/common_voice_8_0 --config ha --split test
+```
+