add the model card

README.md

@@ -1,3 +1,49 @@
 ---
 license: cc-by-4.0
+language: tr
+tags:
+- automatic-speech-recognition
+- mozilla-foundation/common_voice_7_0
+- tr
+- robust-speech-event
+datasets:
+- mozilla-foundation/common_voice_7_0
 ---
+
+# wav2vec2-xls-r-300m-cv7-turkish
+
+## Model description
+This ASR model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on Turkish language.
+
+## Training and evaluation data
+The following datasets were used for finetuning:
+ - [Common Voice 7.0 TR](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) All `validated` split except `test` split was used for training.
+ - [MediaSpeech](https://www.openslr.org/108/)
+
+## Training procedure
+To support both of the datasets above, custom pre-processing and loading steps was performed and [wav2vec2-turkish](https://github.com/mpoyraz/wav2vec2-turkish) repo was used for that purpose.
+
+### Training hyperparameters
+The following hypermaters were used for finetuning:
+- learning_rate 2e-4
+- num_train_epochs 10
+- warmup_steps 500
+- freeze_feature_extractor
+- mask_time_prob 0.1
+- mask_feature_prob 0.05
+- feat_proj_dropout 0.05
+- attention_dropout 0.05
+- final_dropout 0.05
+- activation_dropout 0.05
+- per_device_train_batch_size 8
+- per_device_eval_batch_size 8
+- gradient_accumulation_steps 8
+
+### Framework versions
+- Transformers 4.16.0.dev0
+- Pytorch 1.10.1
+- Datasets 1.17.0
+- Tokenizers 0.10.3
+
+## Language Model
+N-gram language model is trained on a Turkish Wikipedia articles using KenLM and [ngram-lm-wiki](https://github.com/mpoyraz/ngram-lm-wiki) repo was used to generate arpa LM and convert it into binary format.