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--- |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- timit_asr |
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- generated_from_trainer |
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datasets: |
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- timit_asr |
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model-index: |
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- name: sew-d-small-100k-timit |
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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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# sew-d-small-100k-timit |
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This model is a fine-tuned version of [asapp/sew-d-small-100k](https://huggingface.co/asapp/sew-d-small-100k) on the TIMIT_ASR - NA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7541 |
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- Wer: 0.8061 |
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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: 32 |
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- eval_batch_size: 1 |
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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_steps: 1000 |
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- num_epochs: 20.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 4.2068 | 0.69 | 100 | 4.0802 | 1.0 | |
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| 2.9805 | 1.38 | 200 | 2.9792 | 1.0 | |
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| 2.9781 | 2.07 | 300 | 2.9408 | 1.0 | |
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| 2.9655 | 2.76 | 400 | 2.9143 | 1.0 | |
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| 2.8953 | 3.45 | 500 | 2.8775 | 1.0 | |
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| 2.7718 | 4.14 | 600 | 2.7787 | 1.0 | |
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| 2.6711 | 4.83 | 700 | 2.6401 | 0.9786 | |
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| 2.6403 | 5.52 | 800 | 2.5435 | 1.0392 | |
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| 2.4052 | 6.21 | 900 | 2.4580 | 1.0706 | |
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| 2.1708 | 6.9 | 1000 | 2.2800 | 1.0090 | |
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| 2.2555 | 7.59 | 1100 | 2.1493 | 0.9579 | |
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| 2.3673 | 8.28 | 1200 | 2.0709 | 0.9051 | |
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| 2.091 | 8.97 | 1300 | 2.0258 | 0.8926 | |
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| 1.8433 | 9.66 | 1400 | 1.9645 | 0.8243 | |
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| 1.6824 | 10.34 | 1500 | 1.9211 | 0.8707 | |
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| 2.2282 | 11.03 | 1600 | 1.8914 | 0.8695 | |
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| 1.9027 | 11.72 | 1700 | 1.8718 | 0.8343 | |
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| 1.6303 | 12.41 | 1800 | 1.8646 | 0.8232 | |
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| 1.648 | 13.1 | 1900 | 1.8297 | 0.8177 | |
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| 2.0429 | 13.79 | 2000 | 1.8127 | 0.8642 | |
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| 1.8833 | 14.48 | 2100 | 1.8005 | 0.8307 | |
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| 1.5996 | 15.17 | 2200 | 1.7926 | 0.8467 | |
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| 1.4876 | 15.86 | 2300 | 1.7795 | 0.8341 | |
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| 1.8925 | 16.55 | 2400 | 1.7716 | 0.8199 | |
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| 1.814 | 17.24 | 2500 | 1.7846 | 0.8086 | |
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| 1.536 | 17.93 | 2600 | 1.7655 | 0.8019 | |
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| 1.4476 | 18.62 | 2700 | 1.7599 | 0.8070 | |
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| 1.7629 | 19.31 | 2800 | 1.7589 | 0.8119 | |
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| 1.7646 | 20.0 | 2900 | 1.7541 | 0.8061 | |
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### Framework versions |
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- Transformers 4.12.0.dev0 |
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- Pytorch 1.8.1 |
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- Datasets 1.14.1.dev0 |
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- Tokenizers 0.10.3 |
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