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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- evanarlian/common_voice_11_0_id_filtered |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-xls-r-113m-id |
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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: evanarlian/common_voice_11_0_id_filtered |
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type: evanarlian/common_voice_11_0_id_filtered |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.39516649755557604 |
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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-xls-r-113m-id |
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This model is a fine-tuned version of [evanarlian/distil-wav2vec2-xls-r-113m-id](https://huggingface.co/evanarlian/distil-wav2vec2-xls-r-113m-id) on the evanarlian/common_voice_11_0_id_filtered dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3280 |
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- Wer: 0.3952 |
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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: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 24 |
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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_ratio: 0.3 |
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- num_epochs: 25.0 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 3.2512 | 0.92 | 1000 | 2.9098 | 1.0000 | |
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| 2.163 | 1.84 | 2000 | 1.4810 | 0.9941 | |
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| 1.2472 | 2.75 | 3000 | 0.9604 | 0.9196 | |
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| 1.0166 | 3.67 | 4000 | 0.8240 | 0.8498 | |
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| 0.8765 | 4.59 | 5000 | 0.6873 | 0.7741 | |
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| 0.7712 | 5.51 | 6000 | 0.6083 | 0.7111 | |
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| 0.6892 | 6.43 | 7000 | 0.5546 | 0.6592 | |
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| 0.6314 | 7.35 | 8000 | 0.5022 | 0.6108 | |
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| 0.5779 | 8.26 | 9000 | 0.4850 | 0.5825 | |
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| 0.5245 | 9.18 | 10000 | 0.4665 | 0.5538 | |
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| 0.4858 | 10.1 | 11000 | 0.4282 | 0.5279 | |
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| 0.4616 | 11.02 | 12000 | 0.4053 | 0.5082 | |
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| 0.421 | 11.94 | 13000 | 0.3809 | 0.4935 | |
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| 0.4064 | 12.86 | 14000 | 0.3706 | 0.4781 | |
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| 0.3758 | 13.77 | 15000 | 0.3743 | 0.4672 | |
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| 0.3598 | 14.69 | 16000 | 0.3571 | 0.4521 | |
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| 0.3441 | 15.61 | 17000 | 0.3455 | 0.4368 | |
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| 0.3279 | 16.53 | 18000 | 0.3398 | 0.4386 | |
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| 0.3086 | 17.45 | 19000 | 0.3512 | 0.4284 | |
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| 0.3013 | 18.37 | 20000 | 0.3321 | 0.4233 | |
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| 0.2963 | 19.28 | 21000 | 0.3391 | 0.4178 | |
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| 0.2831 | 20.2 | 22000 | 0.3438 | 0.4114 | |
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| 0.2801 | 21.12 | 23000 | 0.3336 | 0.4056 | |
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| 0.2623 | 22.04 | 24000 | 0.3317 | 0.4012 | |
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| 0.263 | 22.96 | 25000 | 0.3280 | 0.4005 | |
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| 0.2529 | 23.88 | 26000 | 0.3268 | 0.3951 | |
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| 0.2492 | 24.79 | 27000 | 0.3280 | 0.3952 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.1 |
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