Create README.md

README.md

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+---
+language:
+- kmr
+license: apache-2.0
+tags:
+- automatic-speech-recognition
+- mozilla-foundation/common_voice_8_0
+- generated_from_trainer
+- kmr
+- robust-speech-event
+- model_for_talk
+datasets:
+- mozilla-foundation/common_voice_8_0
+
+model-index:
+- name: Akashpb13/xlsr_kurmanji_kurdish
+  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: 0.33073206986250464
+       - name: Test CER
+         type: cer
+         value: 0.08035244447163924
+  - 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: 0.33073206986250464
+       - name: Test CER
+         type: cer
+         value: 0.08035244447163924
+---
+
+# 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: 0.292389
+- Wer: 0.388585
+## Model description
+"facebook/wav2vec2-xls-r-300m" was finetuned.
+
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+Training data - 
+Common voice Kurmanji Kurdish 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: 0.000095637994662983496
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 13
+- gradient_accumulation_steps: 16
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+
+
+### Training results
+
+| Step | Training Loss | Validation Loss | Wer      |
+|------|---------------|-----------------|----------|
+| 200  | 4.382500      | 3.183725        | 1.000000 |
+| 400  | 2.870200      | 0.996664        | 0.781117 |
+| 600  | 0.609900      | 0.333755        | 0.445052 |
+| 800  | 0.326800      | 0.305729        | 0.403157 |
+| 1000 | 0.255000      | 0.290734        | 0.391621 |
+| 1200 | 0.226300      | 0.292389        | 0.388585 |
+
+### 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/xlsr_kurmanji_kurdish --dataset mozilla-foundation/common_voice_8_0 --config kmr --split test
+```
+