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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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: model_dialect |
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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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# model_dialect |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8038 |
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- Accuracy: 0.7113 |
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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: 4e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 16 |
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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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| 6.4219 | 0.9455 | 13 | 1.5899 | 0.2610 | |
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| 6.2904 | 1.9636 | 27 | 1.4556 | 0.4550 | |
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| 5.4442 | 2.9818 | 41 | 1.2566 | 0.5219 | |
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| 5.0752 | 4.0 | 55 | 1.1670 | 0.5566 | |
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| 4.748 | 4.9455 | 68 | 1.0790 | 0.5958 | |
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| 4.2202 | 5.9636 | 82 | 1.0372 | 0.6120 | |
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| 4.0075 | 6.9818 | 96 | 0.9833 | 0.6397 | |
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| 3.5847 | 8.0 | 110 | 0.9311 | 0.6721 | |
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| 3.3304 | 8.9455 | 123 | 0.9242 | 0.6420 | |
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| 3.2199 | 9.9636 | 137 | 0.8707 | 0.6928 | |
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| 2.9659 | 10.9818 | 151 | 0.8680 | 0.6767 | |
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| 2.8954 | 12.0 | 165 | 0.8357 | 0.6952 | |
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| 2.6402 | 12.9455 | 178 | 0.8325 | 0.7021 | |
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| 2.4812 | 13.9636 | 192 | 0.8158 | 0.6998 | |
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| 2.4249 | 14.9818 | 206 | 0.8042 | 0.7090 | |
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| 2.4249 | 15.1273 | 208 | 0.8038 | 0.7113 | |
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### Framework versions |
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- Transformers 4.46.0 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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