update model card README.md
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README.md
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---
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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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- f1
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model-index:
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- name: wavlm-basic_s-f-c_8batch_5sec_0.0001lr_unfrozen
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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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# wavlm-basic_s-f-c_8batch_5sec_0.0001lr_unfrozen
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This model is a fine-tuned version of [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8095
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- Accuracy: 0.85
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- F1: 0.8383
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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: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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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: 0.003
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- num_epochs: 1000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 2.2489 | 0.99 | 47 | 2.3092 | 0.1 | 0.0182 |
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| 1.8953 | 2.0 | 95 | 2.1986 | 0.2 | 0.0807 |
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| 1.6269 | 2.99 | 142 | 2.0505 | 0.2667 | 0.1554 |
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| 1.4844 | 4.0 | 190 | 1.7348 | 0.4333 | 0.3482 |
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| 1.2047 | 4.99 | 237 | 1.3970 | 0.5833 | 0.4907 |
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| 1.005 | 6.0 | 285 | 1.3947 | 0.6 | 0.4957 |
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| 0.8541 | 6.99 | 332 | 1.0432 | 0.65 | 0.5830 |
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| 0.7027 | 8.0 | 380 | 1.0033 | 0.7333 | 0.6992 |
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| 0.72 | 8.99 | 427 | 0.9982 | 0.7833 | 0.7657 |
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| 0.5461 | 10.0 | 475 | 1.1170 | 0.6833 | 0.6571 |
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| 0.4415 | 10.99 | 522 | 0.9240 | 0.75 | 0.7402 |
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| 0.4022 | 12.0 | 570 | 0.9522 | 0.7667 | 0.7488 |
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| 0.3664 | 12.99 | 617 | 0.8290 | 0.8333 | 0.8253 |
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| 0.3592 | 14.0 | 665 | 1.0270 | 0.75 | 0.7313 |
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| 0.2985 | 14.99 | 712 | 1.0835 | 0.7667 | 0.7591 |
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| 0.2565 | 16.0 | 760 | 0.9175 | 0.8167 | 0.8090 |
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| 0.2887 | 16.99 | 807 | 0.8095 | 0.85 | 0.8383 |
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| 0.3038 | 18.0 | 855 | 0.8871 | 0.7833 | 0.7763 |
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| 0.242 | 18.99 | 902 | 0.8786 | 0.8 | 0.7875 |
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| 0.1994 | 20.0 | 950 | 1.0309 | 0.7833 | 0.7656 |
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| 0.1569 | 20.99 | 997 | 1.0706 | 0.8 | 0.7886 |
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| 0.1637 | 22.0 | 1045 | 0.9650 | 0.8333 | 0.8249 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.0+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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