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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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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-large-xlsr-53-dialect-classifier |
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results: [] |
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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-xlsr-53-dialect-classifier |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3693 |
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- Accuracy: 0.3605 |
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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: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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_ratio: 0.1 |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.3719 | 0.98 | 21 | 1.3693 | 0.3605 | |
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| 1.371 | 2.0 | 43 | 1.3652 | 0.3605 | |
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| 1.3638 | 2.98 | 64 | 1.3588 | 0.3605 | |
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| 1.3571 | 4.0 | 86 | 1.3508 | 0.3605 | |
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| 1.3446 | 4.98 | 107 | 1.3440 | 0.3605 | |
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| 1.3399 | 6.0 | 129 | 1.3388 | 0.3605 | |
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| 1.3303 | 6.98 | 150 | 1.3340 | 0.3605 | |
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| 1.3305 | 8.0 | 172 | 1.3305 | 0.3605 | |
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| 1.334 | 8.98 | 193 | 1.3267 | 0.3605 | |
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| 1.3303 | 10.0 | 215 | 1.3232 | 0.3605 | |
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| 1.3241 | 10.98 | 236 | 1.3205 | 0.3605 | |
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| 1.317 | 12.0 | 258 | 1.3183 | 0.3605 | |
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| 1.3239 | 12.98 | 279 | 1.3161 | 0.3605 | |
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| 1.3169 | 14.0 | 301 | 1.3144 | 0.3605 | |
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| 1.3129 | 14.98 | 322 | 1.3128 | 0.3605 | |
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| 1.3112 | 16.0 | 344 | 1.3115 | 0.3605 | |
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| 1.3231 | 16.98 | 365 | 1.3107 | 0.3605 | |
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| 1.3115 | 18.0 | 387 | 1.3099 | 0.3605 | |
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| 1.3082 | 18.98 | 408 | 1.3092 | 0.3605 | |
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| 1.3228 | 20.0 | 430 | 1.3085 | 0.3605 | |
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| 1.2872 | 20.98 | 451 | 1.3080 | 0.3605 | |
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| 1.2744 | 22.0 | 473 | 1.3075 | 0.3605 | |
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| 1.2835 | 22.98 | 494 | 1.3070 | 0.3605 | |
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| 1.3213 | 24.0 | 516 | 1.3068 | 0.3605 | |
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| 1.3112 | 24.98 | 537 | 1.3065 | 0.3605 | |
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| 1.3047 | 26.0 | 559 | 1.3062 | 0.3605 | |
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| 1.29 | 26.98 | 580 | 1.3061 | 0.3605 | |
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| 1.3114 | 28.0 | 602 | 1.3060 | 0.3605 | |
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| 1.3123 | 28.98 | 623 | 1.3060 | 0.3605 | |
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| 1.3217 | 29.3 | 630 | 1.3060 | 0.3605 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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