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  ---
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- library_name: transformers
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- tags: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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- ## Model Details
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- ### Model Description
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- ## Uses
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- ### Direct Use
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- ### Downstream Use [optional]
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- ## Bias, Risks, and Limitations
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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- ## Training Details
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- ### Training Data
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- ### Training Procedure
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- #### Preprocessing [optional]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- ## Evaluation
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- ### Results
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- ## Model Examination [optional]
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- ## Technical Specifications [optional]
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- [More Information Needed]
 
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  ---
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+ license: cc-by-nc-4.0
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+ base_model: facebook/mms-1b-all
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - audiofolder
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-large-mms-1b-even-pakendorf
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.7591335595927331
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+ # wav2vec2-large-mms-1b-even-pakendorf
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+ This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: inf
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+ - Wer: 0.7591
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+ - Cer: 0.2779
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+
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+ ## Model description
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+ More information needed
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+ ## Intended uses & limitations
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+ More information needed
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+ ## Training and evaluation data
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+ More information needed
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+ ## Training procedure
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+ ### Training hyperparameters
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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+ - train_batch_size: 4
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 4
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+ - mixed_precision_training: Native AMP
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+ ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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+ | 1.847 | 0.1895 | 300 | inf | 0.9027 | 0.3662 |
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+ | 1.8253 | 0.3790 | 600 | inf | 0.9087 | 0.3658 |
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+ | 1.6956 | 0.5685 | 900 | inf | 0.8723 | 0.3412 |
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+ | 1.6616 | 0.7581 | 1200 | inf | 0.8437 | 0.3209 |
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+ | 1.5962 | 0.9476 | 1500 | inf | 0.8392 | 0.3217 |
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+ | 1.6299 | 1.1371 | 1800 | inf | 0.8447 | 0.3201 |
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+ | 1.5242 | 1.3266 | 2100 | inf | 0.8191 | 0.3076 |
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+ | 1.582 | 1.5161 | 2400 | inf | 0.8157 | 0.3070 |
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+ | 1.5555 | 1.7056 | 2700 | inf | 0.8092 | 0.3061 |
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+ | 1.5476 | 1.8951 | 3000 | inf | 0.7999 | 0.3009 |
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+ | 1.4725 | 2.0846 | 3300 | inf | 0.7945 | 0.2952 |
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+ | 1.4902 | 2.2742 | 3600 | inf | 0.7834 | 0.2936 |
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+ | 1.3984 | 2.4637 | 3900 | inf | 0.7836 | 0.2900 |
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+ | 1.4633 | 2.6532 | 4200 | inf | 0.7942 | 0.2872 |
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+ | 1.4533 | 2.8427 | 4500 | inf | 0.7804 | 0.2863 |
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+ | 1.4814 | 3.0322 | 4800 | inf | 0.7728 | 0.2859 |
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+ | 1.4397 | 3.2217 | 5100 | inf | 0.7693 | 0.2818 |
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+ | 1.4218 | 3.4112 | 5400 | inf | 0.7702 | 0.2831 |
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+ | 1.3655 | 3.6008 | 5700 | inf | 0.7650 | 0.2795 |
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+ | 1.34 | 3.7903 | 6000 | inf | 0.7615 | 0.2792 |
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+ | 1.3351 | 3.9798 | 6300 | inf | 0.7591 | 0.2779 |
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+ ### Framework versions
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+ - Transformers 4.42.0.dev0
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
adapter.eve.safetensors ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:4efa3d821f2b60b81c838e88baae15d00258eaacf5039207b0125010f91aee92
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+ size 8844656