Create README.md

README.md

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+---
+language:
+- sw
+license: apache-2.0
+tags:
+- automatic-speech-recognition
+- mozilla-foundation/common_voice_8_0
+- generated_from_trainer
+- sw
+- robust-speech-event
+- model_for_talk
+datasets:
+- mozilla-foundation/common_voice_8_0
+
+model-index:
+- name: Akashpb13/Swahili_xlsr
+  results:
+  - task: 
+      name: Automatic Speech Recognition 
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 8
+      type: mozilla-foundation/common_voice_8_0
+      args: sw
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 0.11763625454589981
+       - name: Test CER
+         type: cer
+         value: 0.02884228669922436
+  - 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:  0.11763625454589981
+       - name: Test CER
+         type: cer
+         value: 0.02884228669922436
+---
+
+# 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 dev datasets):
+- Loss: 0.159032
+- Wer: 0.187934
+## 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 and dev.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: 80
+- mixed_precision_training: Native AMP
+
+
+### Training results
+
+| Step | Training Loss | Validation Loss | Wer      |
+|------|---------------|-----------------|----------|
+| 500  | 4.810000      | 2.168847        | 0.995747 |
+| 1000 | 0.564200      | 0.209411        | 0.303485 |
+| 1500 | 0.217700      | 0.153959        | 0.239534 |
+| 2000 | 0.150700      | 0.139901        | 0.216327 |
+| 2500 | 0.119400      | 0.137543        | 0.208828 |
+| 3000 | 0.099500      | 0.140921        | 0.203045 |
+| 3500 | 0.087100      | 0.138835        | 0.199649 |
+| 4000 | 0.074600      | 0.141297        | 0.195844 |
+| 4500 | 0.066600      | 0.148560        | 0.194127 |
+| 5000 | 0.060400      | 0.151214        | 0.194388 |
+| 5500 | 0.054400      | 0.156072        | 0.192187 |
+| 6000 | 0.051100      | 0.154726        | 0.190322 |
+| 6500 | 0.048200      | 0.159847        | 0.189538 |
+| 7000 | 0.046400      | 0.158727        | 0.188307 |
+| 7500 | 0.046500      | 0.159032        | 0.187934 |
+
+
+### 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/Swahili_xlsr --dataset mozilla-foundation/common_voice_8_0 --config sw --split test
+```
+