Downloads · 30 days
12
32% of all-time downloads
wav2vec2-common_voice-tr-output
Robinjmf/wav2vec2-common_voice-tr-output
wav2vec2-common_voice-tr-output is a automatic speech recognition model from Robinjmf. 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
37
Public
Repo size
32.8 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.3 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- May 19, 2023
- Updated
- May 30, 2023
- SHA
- 2e7c8cc1
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-common_voice-tr-output
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:
- Loss: 0.3776
- Wer: 0.3243
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.92 | 100 | 3.6020 | 1.0 |
| No log | 1.83 | 200 | 2.9971 | 0.9999 |
| No log | 2.75 | 300 | 0.9174 | 0.7772 |
| No log | 3.67 | 400 | 0.5668 | 0.6356 |
| 3.1619 | 4.59 | 500 | 0.4949 | 0.5256 |
| 3.1619 | 5.5 | 600 | 0.4516 | 0.4744 |
| 3.1619 | 6.42 | 700 | 0.4291 | 0.4575 |
| 3.1619 | 7.34 | 800 | 0.4330 | 0.4273 |
| 3.1619 | 8.26 | 900 | 0.4016 | 0.4145 |
| 0.2261 | 9.17 | 1000 | 0.4214 | 0.4005 |
| 0.2261 | 10.09 | 1100 | 0.4093 | 0.3946 |
| 0.2261 | 11.01 | 1200 | 0.4051 | 0.3917 |
| 0.2261 | 11.93 | 1300 | 0.3908 | 0.3719 |
| 0.2261 | 12.84 | 1400 | 0.3850 | 0.3603 |
| 0.1119 | 13.76 | 1500 | 0.3967 | 0.3645 |
| 0.1119 | 14.68 | 1600 | 0.3821 | 0.3526 |
| 0.1119 | 15.6 | 1700 | 0.3919 | 0.3519 |
| 0.1119 | 16.51 | 1800 | 0.3763 | 0.3366 |
| 0.1119 | 17.43 | 1900 | 0.3682 | 0.3349 |
| 0.074 | 18.35 | 2000 | 0.3753 | 0.3323 |
| 0.074 | 19.27 | 2100 | 0.3753 | 0.3267 |
Framework versions
- Transformers 4.28.1
- Pytorch 1.12.1+cu102
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Languages
- tr
- Created
- May 19, 2023
- Updated
- May 30, 2023