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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: output |
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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: common_voice_13_0 |
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type: common_voice_13_0 |
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config: hi |
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split: test |
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args: hi |
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metrics: |
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- name: Wer |
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type: wer |
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value: 1.019918009027289 |
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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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# output |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co./facebook/wav2vec2-xls-r-300m) on the common_voice_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7883 |
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- Wer: 1.0199 |
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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: 0.0003 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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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: 500 |
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- num_epochs: 30 |
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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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| 5.92 | 0.95 | 400 | 2.9522 | 1.0026 | |
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| 1.0435 | 1.89 | 800 | 0.8608 | 1.0552 | |
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| 0.5354 | 2.84 | 1200 | 0.7762 | 1.0169 | |
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| 0.404 | 3.79 | 1600 | 0.6984 | 1.0293 | |
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| 0.3301 | 4.73 | 2000 | 0.6811 | 1.0217 | |
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| 0.2745 | 5.68 | 2400 | 0.7027 | 1.0308 | |
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| 0.2346 | 6.63 | 2800 | 0.7296 | 1.0185 | |
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| 0.2096 | 7.57 | 3200 | 0.7148 | 1.0294 | |
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| 0.1912 | 8.52 | 3600 | 0.7109 | 1.0335 | |
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| 0.172 | 9.47 | 4000 | 0.7894 | 1.0252 | |
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| 0.1567 | 10.41 | 4400 | 0.7592 | 1.0219 | |
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| 0.1457 | 11.36 | 4800 | 0.8030 | 1.0141 | |
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| 0.1337 | 12.31 | 5200 | 0.7811 | 1.0237 | |
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| 0.1288 | 13.25 | 5600 | 0.7703 | 1.0188 | |
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| 0.1165 | 14.2 | 6000 | 0.7728 | 1.0199 | |
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| 0.105 | 15.15 | 6400 | 0.7934 | 1.0206 | |
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| 0.1028 | 16.09 | 6800 | 0.7978 | 1.0185 | |
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| 0.092 | 17.04 | 7200 | 0.8276 | 1.0289 | |
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| 0.0901 | 17.99 | 7600 | 0.7881 | 1.0202 | |
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| 0.0818 | 18.93 | 8000 | 0.7847 | 1.0162 | |
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| 0.0801 | 19.88 | 8400 | 0.8142 | 1.0230 | |
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| 0.0768 | 20.83 | 8800 | 0.7735 | 1.0215 | |
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| 0.0721 | 21.78 | 9200 | 0.7941 | 1.0227 | |
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| 0.0658 | 22.72 | 9600 | 0.8100 | 1.0219 | |
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| 0.0627 | 23.67 | 10000 | 0.7592 | 1.0196 | |
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| 0.0591 | 24.62 | 10400 | 0.8028 | 1.0210 | |
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| 0.0537 | 25.56 | 10800 | 0.8019 | 1.0253 | |
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| 0.0507 | 26.51 | 11200 | 0.7951 | 1.0212 | |
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| 0.0495 | 27.46 | 11600 | 0.7893 | 1.0207 | |
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| 0.0466 | 28.4 | 12000 | 0.7854 | 1.0188 | |
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| 0.0431 | 29.35 | 12400 | 0.7883 | 1.0199 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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