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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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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: tachiwin_totonac |
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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: ljcamargo--totonac_alpha_1 |
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split: test |
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args: ljcamargo--totonac_alpha_1 |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.6465189873417722 |
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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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# tachiwin_totonac |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7535 |
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- Wer: 0.6465 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 90 |
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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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| 5.1063 | 5.19 | 200 | 2.9834 | 1.0 | |
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| 2.9016 | 10.39 | 400 | 2.4405 | 0.9959 | |
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| 1.7606 | 15.58 | 600 | 1.1942 | 0.8532 | |
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| 1.0549 | 20.78 | 800 | 1.1132 | 0.7788 | |
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| 0.7553 | 25.97 | 1000 | 1.1224 | 0.6899 | |
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| 0.6639 | 31.51 | 1200 | 1.2641 | 0.7082 | |
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| 0.5344 | 36.7 | 1400 | 1.3247 | 0.6835 | |
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| 0.4527 | 41.9 | 1600 | 1.3915 | 0.7022 | |
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| 0.3839 | 47.09 | 1800 | 1.4051 | 0.6791 | |
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| 0.3065 | 52.29 | 2000 | 1.3899 | 0.6706 | |
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| 0.2714 | 57.48 | 2200 | 1.5455 | 0.6573 | |
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| 0.2437 | 62.68 | 2400 | 1.6798 | 0.6601 | |
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| 0.2103 | 67.87 | 2600 | 1.7406 | 0.6674 | |
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| 0.1899 | 73.06 | 2800 | 1.7625 | 0.6522 | |
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| 0.1841 | 78.26 | 3000 | 1.7443 | 0.6535 | |
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| 0.1544 | 83.45 | 3200 | 1.7405 | 0.6465 | |
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| 0.1461 | 88.65 | 3400 | 1.7535 | 0.6465 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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