Downloads · 30 days
7
11% of all-time downloads
wav2vec2-large-xlsr-53-br
gweltou/wav2vec2-large-xlsr-53-br
wav2vec2-large-xlsr-53-br is a automatic speech recognition model from gweltou. 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. --
All-time downloads
61
Public
Parameters
315M
20.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.3 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Jan 18, 2024
- Updated
- Jun 3, 2024
- SHA
- 5944d722
Base models
Datasets
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. -->
wav2vec2-large-xlsr-53-br
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice_15_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7879
- Wer: 54.7151
- Cer: 19.2493
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: 6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 6.3257 | 2.18 | 500 | 3.0700 | 100.0 | 99.0871 |
| 2.2071 | 4.36 | 1000 | 1.1541 | 80.0449 | 29.4230 |
| 1.0019 | 6.54 | 1500 | 0.8986 | 69.2059 | 24.3938 |
| 0.7796 | 8.71 | 2000 | 0.8015 | 63.3737 | 22.1296 |
| 0.6677 | 10.89 | 2500 | 0.8014 | 61.4984 | 21.4568 |
| 0.5937 | 13.07 | 3000 | 0.7623 | 58.9323 | 20.4929 |
| 0.5454 | 15.25 | 3500 | 0.7975 | 57.8466 | 20.2585 |
| 0.5075 | 17.43 | 4000 | 0.7831 | 56.7250 | 19.7879 |
| 0.4837 | 19.61 | 4500 | 0.7902 | 55.9623 | 19.5101 |
| 0.4529 | 21.79 | 5000 | 0.7851 | 54.9753 | 19.0924 |
| 0.4381 | 23.97 | 5500 | 0.7865 | 55.1727 | 19.3211 |
| 0.4208 | 26.14 | 6000 | 0.8168 | 55.1817 | 19.3967 |
| 0.4197 | 28.32 | 6500 | 0.7879 | 54.7151 | 19.2493 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Jan 18, 2024
- Updated
- Jun 3, 2024