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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: wav2vec2-base-timit-fine-tuned |
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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-timit-fine-tuned |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the TIMIT_ASR - NA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3457 |
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- Wer: 0.2151 |
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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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| 3.1621 | 0.69 | 100 | 3.1102 | 1.0 | |
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| 2.9592 | 1.38 | 200 | 2.9603 | 1.0 | |
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| 2.9116 | 2.07 | 300 | 2.8921 | 1.0 | |
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| 2.1332 | 2.76 | 400 | 1.9718 | 0.9958 | |
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| 0.8477 | 3.45 | 500 | 0.7813 | 0.5237 | |
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| 0.4251 | 4.14 | 600 | 0.5166 | 0.3982 | |
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| 0.3743 | 4.83 | 700 | 0.4400 | 0.3578 | |
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| 0.4194 | 5.52 | 800 | 0.4077 | 0.3370 | |
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| 0.23 | 6.21 | 900 | 0.4018 | 0.3142 | |
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| 0.1554 | 6.9 | 1000 | 0.3623 | 0.2995 | |
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| 0.1511 | 7.59 | 1100 | 0.3433 | 0.2697 | |
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| 0.1983 | 8.28 | 1200 | 0.3539 | 0.2715 | |
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| 0.1443 | 8.97 | 1300 | 0.3622 | 0.2551 | |
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| 0.0971 | 9.66 | 1400 | 0.3580 | 0.2519 | |
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| 0.0764 | 10.34 | 1500 | 0.3529 | 0.2437 | |
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| 0.1203 | 11.03 | 1600 | 0.3455 | 0.2431 | |
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| 0.0881 | 11.72 | 1700 | 0.3648 | 0.2415 | |
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| 0.0521 | 12.41 | 1800 | 0.3564 | 0.2320 | |
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| 0.0434 | 13.1 | 1900 | 0.3485 | 0.2270 | |
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| 0.0864 | 13.79 | 2000 | 0.3517 | 0.2228 | |
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| 0.0651 | 14.48 | 2100 | 0.3506 | 0.2285 | |
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| 0.0423 | 15.17 | 2200 | 0.3428 | 0.2247 | |
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| 0.0302 | 15.86 | 2300 | 0.3372 | 0.2198 | |
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| 0.0548 | 16.55 | 2400 | 0.3496 | 0.2196 | |
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| 0.0674 | 17.24 | 2500 | 0.3407 | 0.2166 | |
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| 0.0291 | 17.93 | 2600 | 0.3512 | 0.2171 | |
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| 0.0298 | 18.62 | 2700 | 0.3363 | 0.2158 | |
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| 0.0419 | 19.31 | 2800 | 0.3493 | 0.2145 | |
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| 0.046 | 20.0 | 2900 | 0.3457 | 0.2151 | |
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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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