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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: my_awesome_speach_model |
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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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# my_awesome_speach_model |
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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: 0.8215 |
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- Accuracy: 0.6154 |
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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: 3e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 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: 40 |
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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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| No log | 0.8889 | 6 | 0.6905 | 0.6923 | |
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| 0.6936 | 1.9259 | 13 | 0.7083 | 0.3077 | |
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| 0.6859 | 2.9630 | 20 | 0.7061 | 0.3846 | |
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| 0.6859 | 4.0 | 27 | 0.7065 | 0.4615 | |
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| 0.6738 | 4.8889 | 33 | 0.7058 | 0.5385 | |
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| 0.6487 | 5.9259 | 40 | 0.7190 | 0.5385 | |
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| 0.6487 | 6.9630 | 47 | 0.6488 | 0.6154 | |
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| 0.5804 | 8.0 | 54 | 0.6696 | 0.6154 | |
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| 0.6227 | 8.8889 | 60 | 0.7988 | 0.3846 | |
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| 0.6227 | 9.9259 | 67 | 0.6253 | 0.6923 | |
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| 0.6318 | 10.9630 | 74 | 0.6760 | 0.6154 | |
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| 0.6617 | 12.0 | 81 | 0.9642 | 0.3077 | |
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| 0.6617 | 12.8889 | 87 | 0.7761 | 0.5385 | |
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| 0.6052 | 13.9259 | 94 | 0.8490 | 0.4615 | |
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| 0.5238 | 14.9630 | 101 | 0.7963 | 0.4615 | |
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| 0.5238 | 16.0 | 108 | 0.7485 | 0.5385 | |
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| 0.452 | 16.8889 | 114 | 0.7720 | 0.5385 | |
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| 0.3813 | 17.9259 | 121 | 0.7478 | 0.6154 | |
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| 0.3813 | 18.9630 | 128 | 0.8406 | 0.6154 | |
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| 0.4809 | 20.0 | 135 | 0.6624 | 0.6923 | |
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| 0.3698 | 20.8889 | 141 | 0.7520 | 0.6154 | |
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| 0.3698 | 21.9259 | 148 | 0.8275 | 0.5385 | |
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| 0.2959 | 22.9630 | 155 | 0.8472 | 0.5385 | |
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| 0.3976 | 24.0 | 162 | 1.0899 | 0.4615 | |
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| 0.3976 | 24.8889 | 168 | 0.8758 | 0.5385 | |
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| 0.3788 | 25.9259 | 175 | 0.5872 | 0.7692 | |
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| 0.3511 | 26.9630 | 182 | 0.7996 | 0.6154 | |
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| 0.3511 | 28.0 | 189 | 0.7726 | 0.6154 | |
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| 0.2797 | 28.8889 | 195 | 0.7310 | 0.6923 | |
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| 0.2445 | 29.9259 | 202 | 0.7223 | 0.6154 | |
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| 0.2445 | 30.9630 | 209 | 0.7139 | 0.6923 | |
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| 0.2299 | 32.0 | 216 | 0.7540 | 0.6923 | |
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| 0.2101 | 32.8889 | 222 | 0.7878 | 0.6154 | |
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| 0.2101 | 33.9259 | 229 | 0.7942 | 0.6154 | |
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| 0.2043 | 34.9630 | 236 | 0.8193 | 0.6154 | |
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| 0.1638 | 35.5556 | 240 | 0.8215 | 0.6154 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.20.3 |
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