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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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