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Fine_Tuned_XLSR_English
Sania67/Fine_Tuned_XLSR_English
Fine_Tuned_XLSR_English is a automatic speech recognition model from Sania67. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Aug 26, 2022
- Updated
- Aug 26, 2022
- SHA
- e6b0ec49
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
Fine_Tuned_XLSR_English
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the timit_asr dataset. It achieves the following results on the evaluation set:
- Loss: 0.4033
- Wer: 0.3163
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.3757 | 1.0 | 500 | 3.1570 | 1.0 |
| 2.4891 | 2.01 | 1000 | 0.9252 | 0.8430 |
| 0.8725 | 3.01 | 1500 | 0.4581 | 0.4931 |
| 0.544 | 4.02 | 2000 | 0.3757 | 0.4328 |
| 0.4043 | 5.02 | 2500 | 0.3621 | 0.4087 |
| 0.3376 | 6.02 | 3000 | 0.3682 | 0.3931 |
| 0.2937 | 7.03 | 3500 | 0.3541 | 0.3743 |
| 0.2573 | 8.03 | 4000 | 0.3565 | 0.3593 |
| 0.2257 | 9.04 | 4500 | 0.3634 | 0.3654 |
| 0.215 | 10.04 | 5000 | 0.3695 | 0.3537 |
| 0.1879 | 11.04 | 5500 | 0.3690 | 0.3486 |
| 0.1599 | 12.05 | 6000 | 0.3743 | 0.3490 |
| 0.1499 | 13.05 | 6500 | 0.4108 | 0.3424 |
| 0.147 | 14.06 | 7000 | 0.4048 | 0.3400 |
| 0.1355 | 15.06 | 7500 | 0.3988 | 0.3357 |
| 0.1278 | 16.06 | 8000 | 0.3672 | 0.3384 |
| 0.1189 | 17.07 | 8500 | 0.4011 | 0.3340 |
| 0.1089 | 18.07 | 9000 | 0.3948 | 0.3300 |
| 0.1039 | 19.08 | 9500 | 0.4062 | 0.3317 |
| 0.0971 | 20.08 | 10000 | 0.4041 | 0.3252 |
| 0.0902 | 21.08 | 10500 | 0.4112 | 0.3301 |
| 0.0883 | 22.09 | 11000 | 0.4154 | 0.3292 |
| 0.0864 | 23.09 | 11500 | 0.3746 | 0.3189 |
| 0.0746 | 24.1 | 12000 | 0.3991 | 0.3230 |
| 0.0711 | 25.1 | 12500 | 0.3916 | 0.3200 |
| 0.0712 | 26.1 | 13000 | 0.4024 | 0.3193 |
| 0.0663 | 27.11 | 13500 | 0.3976 | 0.3184 |
| 0.0626 | 28.11 | 14000 | 0.4046 | 0.3168 |
| 0.0641 | 29.12 | 14500 | 0.4033 | 0.3163 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.12.1+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Aug 26, 2022
- Updated
- Aug 26, 2022