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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-large-xlsr-53
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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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- precision
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- recall
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- f1
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model-index:
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- name: SER_wav2vec2-large-xlsr-53_240303
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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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# SER_wav2vec2-large-xlsr-53_240303
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.7923
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- Accuracy: 0.2408
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- Precision: 0.2324
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- Recall: 0.2466
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- F1: 0.2226
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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: 0.0001
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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: 3
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- total_train_batch_size: 12
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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: 8
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 1.9297 | 1.0 | 101 | 1.9452 | 0.1233 | 0.0306 | 0.1468 | 0.0454 |
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| 1.9114 | 2.0 | 202 | 1.9115 | 0.1773 | 0.1501 | 0.1803 | 0.1323 |
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| 1.7863 | 3.0 | 303 | 1.8564 | 0.2081 | 0.1117 | 0.2193 | 0.1336 |
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| 1.8439 | 4.0 | 404 | 1.8590 | 0.2042 | 0.2196 | 0.2156 | 0.1755 |
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| 1.9361 | 5.0 | 505 | 1.8375 | 0.2081 | 0.2617 | 0.2213 | 0.1573 |
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| 1.7572 | 6.0 | 606 | 1.8081 | 0.2100 | 0.2018 | 0.2214 | 0.1841 |
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| 1.6715 | 7.0 | 707 | 1.8131 | 0.2389 | 0.2263 | 0.2442 | 0.2129 |
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| 1.6687 | 8.0 | 808 | 1.7923 | 0.2408 | 0.2324 | 0.2466 | 0.2226 |
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### Framework versions
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- Transformers 4.38.1
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- Pytorch 2.2.1
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- Datasets 2.17.1
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- Tokenizers 0.15.2
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