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README.md
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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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datasets:
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- common_language
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metrics:
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- accuracy
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model-index:
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- name: wav2vec2-base-lang-id
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results:
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- task:
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name: Audio Classification
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type: audio-classification
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dataset:
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name: common_language
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type: common_language
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config: full
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split: validation
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args: full
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7800611413043478
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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-base-lang-id
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_language dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2554
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- Accuracy: 0.7801
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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: 8
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- eval_batch_size: 1
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- seed: 0
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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- optimizer: Use OptimizerNames.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: 10.0
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- mixed_precision_training: Native AMP
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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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| 2.58 | 0.9989 | 693 | 2.5609 | 0.2899 |
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| 1.8581 | 1.9989 | 1386 | 2.1486 | 0.4008 |
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| 1.3784 | 2.9989 | 2079 | 1.5906 | 0.5666 |
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| 0.976 | 3.9989 | 2772 | 1.4036 | 0.6318 |
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| 0.6109 | 4.9989 | 3465 | 1.3022 | 0.6695 |
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| 0.4357 | 5.9989 | 4158 | 1.2386 | 0.7138 |
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| 0.23 | 6.9989 | 4851 | 1.3078 | 0.7221 |
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| 0.1461 | 7.9989 | 5544 | 1.2247 | 0.7534 |
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| 0.0567 | 8.9989 | 6237 | 1.3279 | 0.7646 |
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| 0.0375 | 9.9989 | 6930 | 1.2554 | 0.7801 |
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### Framework versions
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- Transformers 4.49.0.dev0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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