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End of training
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README.md
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---
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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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- audiofolder
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metrics:
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- accuracy
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model-index:
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- name: WAVLM_TITML_IDN_model
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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: audiofolder
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type: audiofolder
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config: default
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split: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.22904191616766467
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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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# WAVLM_TITML_IDN_model
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 4.0267
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- Accuracy: 0.2290
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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: 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: 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: 10
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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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| 8.0756 | 0.98 | 31 | 7.9311 | 0.0501 |
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| 7.5146 | 2.0 | 63 | 7.3364 | 0.1302 |
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| 6.9603 | 2.98 | 94 | 6.7363 | 0.1460 |
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| 6.364 | 4.0 | 126 | 6.0966 | 0.1714 |
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| 5.786 | 4.98 | 157 | 5.5013 | 0.2238 |
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| 5.2431 | 6.0 | 189 | 4.9557 | 0.2006 |
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| 4.6574 | 6.98 | 220 | 4.5298 | 0.2096 |
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| 4.3323 | 8.0 | 252 | 4.2341 | 0.2283 |
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| 4.1522 | 8.98 | 283 | 4.0721 | 0.2253 |
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| 4.0934 | 9.84 | 310 | 4.0267 | 0.2290 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.5
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- Tokenizers 0.14.1
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