|  | --- | 
					
						
						|  | language: | 
					
						
						|  | - tr | 
					
						
						|  | license: cc-by-nc-4.0 | 
					
						
						|  | tags: | 
					
						
						|  | - automatic-speech-recognition | 
					
						
						|  | - common_voice | 
					
						
						|  | - generated_from_trainer | 
					
						
						|  | - mms | 
					
						
						|  | datasets: | 
					
						
						|  | - common_voice | 
					
						
						|  | metrics: | 
					
						
						|  | - wer | 
					
						
						|  | model-index: | 
					
						
						|  | - name: wav2vec2-common_voice-tr-mms-demo-3 | 
					
						
						|  | results: | 
					
						
						|  | - task: | 
					
						
						|  | name: Automatic Speech Recognition | 
					
						
						|  | type: automatic-speech-recognition | 
					
						
						|  | dataset: | 
					
						
						|  | name: COMMON_VOICE - TR | 
					
						
						|  | type: common_voice | 
					
						
						|  | config: tr | 
					
						
						|  | split: test | 
					
						
						|  | args: 'Config: tr, Training split: train+validation, Eval split: test' | 
					
						
						|  | metrics: | 
					
						
						|  | - name: Wer | 
					
						
						|  | type: wer | 
					
						
						|  | value: 0.2267388417934838 | 
					
						
						|  | --- | 
					
						
						|  |  | 
					
						
						|  | <!-- 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. --> | 
					
						
						|  |  | 
					
						
						|  | # wav2vec2-common_voice-tr-mms-demo | 
					
						
						|  |  | 
					
						
						|  | This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the COMMON_VOICE - TR dataset. | 
					
						
						|  | It achieves the following results on the evaluation set: | 
					
						
						|  | - Loss: 0.1532 | 
					
						
						|  | - Wer: 0.2267 | 
					
						
						|  |  | 
					
						
						|  | ## 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: 0.001 | 
					
						
						|  | - train_batch_size: 32 | 
					
						
						|  | - eval_batch_size: 8 | 
					
						
						|  | - seed: 42 | 
					
						
						|  | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | 
					
						
						|  | - lr_scheduler_type: linear | 
					
						
						|  | - lr_scheduler_warmup_steps: 100 | 
					
						
						|  | - num_epochs: 4.0 | 
					
						
						|  |  | 
					
						
						|  | ### Training results | 
					
						
						|  |  | 
					
						
						|  | | Training Loss | Epoch | Step | Validation Loss | Wer    | | 
					
						
						|  | |:-------------:|:-----:|:----:|:---------------:|:------:| | 
					
						
						|  | | No log        | 0.92  | 100  | 0.1822          | 0.2605 | | 
					
						
						|  | | No log        | 1.83  | 200  | 0.1620          | 0.2389 | | 
					
						
						|  | | No log        | 2.75  | 300  | 0.1581          | 0.2318 | | 
					
						
						|  | | No log        | 3.67  | 400  | 0.1535          | 0.2270 | | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | ### Framework versions | 
					
						
						|  |  | 
					
						
						|  | - Transformers 4.31.0.dev0 | 
					
						
						|  | - Pytorch 2.0.1+cu117 | 
					
						
						|  | - Datasets 2.12.0 | 
					
						
						|  | - Tokenizers 0.13.3 |