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README.md
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---
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library_name: transformers
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license: cc-by-sa-4.0
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base_model: airesearch/wav2vec2-large-xlsr-53-th
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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-th-speech-emotion-recognition
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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-th-speech-emotion-recognition
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This model is a fine-tuned version of [airesearch/wav2vec2-large-xlsr-53-th](https://huggingface.co/airesearch/wav2vec2-large-xlsr-53-th) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8209
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- Accuracy: 0.6849
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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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| 1.4531 | 1.0 | 89 | 1.3187 | 0.4384 |
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| 1.1932 | 2.0 | 178 | 1.1075 | 0.5416 |
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| 0.984 | 3.0 | 267 | 0.9787 | 0.6024 |
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| 0.9603 | 4.0 | 356 | 0.9281 | 0.6224 |
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| 0.8789 | 5.0 | 445 | 0.9141 | 0.6361 |
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| 0.9113 | 6.0 | 534 | 0.8611 | 0.6568 |
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| 0.8453 | 7.0 | 623 | 0.8444 | 0.6656 |
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| 0.7558 | 8.0 | 712 | 0.8257 | 0.6776 |
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| 0.784 | 9.0 | 801 | 0.8341 | 0.6783 |
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| 0.7566 | 10.0 | 890 | 0.8209 | 0.6849 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.19.1
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