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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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- librispeech_asr |
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- generated_from_trainer |
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model-index: |
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- name: sew-mid-100k-librispeech-clean-100h-ft |
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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-mid-100k-librispeech-clean-100h-ft |
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This model is a fine-tuned version of [asapp/sew-mid-100k](https://huggingface.co/asapp/sew-mid-100k) on the LIBRISPEECH_ASR - CLEAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.9609 |
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- Wer: 1.0 |
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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: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 64 |
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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: 500 |
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- num_epochs: 3.0 |
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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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| 2.9558 | 0.11 | 100 | 2.9238 | 1.0 | |
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| 2.8978 | 0.22 | 200 | 2.9614 | 1.0 | |
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| 2.9267 | 0.34 | 300 | 3.3049 | 1.0 | |
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| 3.1351 | 0.45 | 400 | 2.9246 | 1.0 | |
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| 3.4365 | 0.56 | 500 | 4.2798 | 1.0 | |
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| 3.1861 | 0.67 | 600 | 4.0740 | 1.0 | |
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| 2.914 | 0.78 | 700 | 3.6876 | 1.0 | |
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| 3.0777 | 0.9 | 800 | 3.7421 | 1.0 | |
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| 2.8181 | 1.01 | 900 | 3.7825 | 1.0 | |
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| 2.8211 | 1.12 | 1000 | 3.9630 | 1.0 | |
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| 2.8209 | 1.23 | 1100 | 3.9605 | 1.0 | |
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| 2.8304 | 1.35 | 1200 | 3.7005 | 1.0 | |
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| 2.85 | 1.46 | 1300 | 3.5085 | 1.0 | |
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| 2.8509 | 1.57 | 1400 | 3.6157 | 1.0 | |
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| 2.8643 | 1.68 | 1500 | 3.5116 | 1.0 | |
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| 2.8265 | 1.79 | 1600 | 3.6322 | 1.0 | |
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| 2.8032 | 1.91 | 1700 | 4.0325 | 1.0 | |
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| 2.8053 | 2.02 | 1800 | 4.0125 | 1.0 | |
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| 2.819 | 2.13 | 1900 | 3.7971 | 1.0 | |
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| 2.8163 | 2.24 | 2000 | 3.9216 | 1.0 | |
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| 2.8214 | 2.35 | 2100 | 3.9178 | 1.0 | |
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| 2.8116 | 2.47 | 2200 | 3.9604 | 1.0 | |
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| 2.81 | 2.58 | 2300 | 3.9279 | 1.0 | |
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| 2.8051 | 2.69 | 2400 | 3.9737 | 1.0 | |
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| 2.8179 | 2.8 | 2500 | 3.9725 | 1.0 | |
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| 2.8098 | 2.91 | 2600 | 3.9591 | 1.0 | |
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### Framework versions |
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- Transformers 4.12.0.dev0 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.13.4.dev0 |
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- Tokenizers 0.10.3 |
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