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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-all-lingala-ojpl |
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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: 0.2697881828316611 |
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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-all-lingala-ojpl |
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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: 0.8394 |
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- Wer: 0.2698 |
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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: 1 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.5442 | 0.13 | 100 | 0.9396 | 0.3307 | |
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| 0.9882 | 0.27 | 200 | 0.9189 | 0.3389 | |
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| 0.5845 | 0.4 | 300 | 0.9322 | 0.3129 | |
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| 0.4162 | 0.54 | 400 | 1.0742 | 0.2939 | |
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| 0.506 | 0.67 | 500 | 0.9626 | 0.3077 | |
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| 0.8789 | 0.81 | 600 | 1.0502 | 0.3055 | |
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| 0.6166 | 0.94 | 700 | 0.9560 | 0.2984 | |
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| 0.4101 | 1.08 | 800 | 0.9520 | 0.2995 | |
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| 0.6536 | 1.21 | 900 | 1.1213 | 0.2988 | |
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| 0.4921 | 1.34 | 1000 | 1.0319 | 0.3010 | |
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| 0.856 | 1.48 | 1100 | 0.9514 | 0.3043 | |
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| 0.4479 | 1.61 | 1200 | 0.9079 | 0.2843 | |
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| 0.7249 | 1.75 | 1300 | 0.9612 | 0.2895 | |
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| 0.5384 | 1.88 | 1400 | 0.9050 | 0.2928 | |
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| 0.709 | 2.02 | 1500 | 0.9844 | 0.2735 | |
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| 0.6575 | 2.15 | 1600 | 0.9377 | 0.2772 | |
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| 0.6115 | 2.28 | 1700 | 0.9690 | 0.2876 | |
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| 0.3119 | 2.42 | 1800 | 0.9222 | 0.2798 | |
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| 0.3591 | 2.55 | 1900 | 0.9358 | 0.2783 | |
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| 0.3979 | 2.69 | 2000 | 0.9156 | 0.2702 | |
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| 0.7541 | 2.82 | 2100 | 0.8838 | 0.2761 | |
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| 0.81 | 2.96 | 2200 | 0.8460 | 0.2813 | |
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| 0.2224 | 3.09 | 2300 | 0.9377 | 0.2694 | |
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| 0.2338 | 3.23 | 2400 | 0.8870 | 0.2746 | |
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| 0.5315 | 3.36 | 2500 | 0.8782 | 0.2672 | |
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| 0.4045 | 3.49 | 2600 | 0.8811 | 0.2653 | |
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| 0.4874 | 3.63 | 2700 | 0.9059 | 0.2620 | |
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| 0.304 | 3.76 | 2800 | 0.8801 | 0.2690 | |
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| 1.4688 | 3.9 | 2900 | 0.8394 | 0.2698 | |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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