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update model card README.md
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- bayartsogt/mongolian_speech_commands
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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: wav2vec2-base-mn-pretrain-42h-finetuned-speech-commands
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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-base-mn-pretrain-42h-finetuned-speech-commands
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This model is a fine-tuned version of [bayartsogt/wav2vec2-base-mn-pretrain-42h](https://huggingface.co/bayartsogt/wav2vec2-base-mn-pretrain-42h) on the Mongolian Speech Commands dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1007
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- Accuracy: 0.9762
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- F1: 0.9758
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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: 5e-05
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 42
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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: 20
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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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| 2.2273 | 1.0 | 17 | 2.2714 | 0.1190 | 0.0253 |
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| 1.7478 | 2.0 | 34 | 1.2036 | 0.8452 | 0.8242 |
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| 0.775 | 3.0 | 51 | 0.4755 | 0.9524 | 0.9526 |
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| 0.4738 | 4.0 | 68 | 0.2056 | 0.9881 | 0.9878 |
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| 0.3146 | 5.0 | 85 | 0.1485 | 0.9762 | 0.9765 |
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| 0.2677 | 6.0 | 102 | 0.1277 | 0.9762 | 0.9758 |
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| 0.2636 | 7.0 | 119 | 0.0919 | 0.9881 | 0.9880 |
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| 0.2122 | 8.0 | 136 | 0.0903 | 0.9762 | 0.9758 |
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| 0.1817 | 9.0 | 153 | 0.0782 | 0.9881 | 0.9880 |
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| 0.198 | 10.0 | 170 | 0.0982 | 0.9762 | 0.9758 |
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| 0.1436 | 11.0 | 187 | 0.1053 | 0.9762 | 0.9758 |
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| 0.1111 | 12.0 | 204 | 0.1004 | 0.9762 | 0.9758 |
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| 0.1607 | 13.0 | 221 | 0.1176 | 0.9762 | 0.9758 |
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| 0.1209 | 14.0 | 238 | 0.1097 | 0.9762 | 0.9758 |
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| 0.0974 | 15.0 | 255 | 0.1136 | 0.9762 | 0.9758 |
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| 0.1351 | 16.0 | 272 | 0.0986 | 0.9762 | 0.9758 |
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| 0.1008 | 17.0 | 289 | 0.1010 | 0.9762 | 0.9758 |
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| 0.097 | 18.0 | 306 | 0.0781 | 0.9762 | 0.9758 |
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| 0.0806 | 19.0 | 323 | 0.1106 | 0.9762 | 0.9758 |
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| 0.0744 | 20.0 | 340 | 0.1007 | 0.9762 | 0.9758 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.0
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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