Downloads · 30 days
25
23% of all-time downloads
wav2vec_arabic_mdd_experiment2
nrshoudi/wav2vec_arabic_mdd_experiment2
wav2vec_arabic_mdd_experiment2 is a automatic speech recognition model from nrshoudi. 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
108
Public
Parameters
315M
78.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.3 GB · 50%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Oct 30, 2023
- Updated
- Nov 3, 2023
- SHA
- 2c07068e
Base models
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. -->
wav2vec_arabic_mdd_experiment2
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2053
- Per: 0.1078
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 6
- 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: 250
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Per |
|---|---|---|---|---|
| 6.6285 | 1.0 | 102 | 2.6113 | 1.0 |
| 2.3387 | 2.0 | 205 | 2.3622 | 1.0 |
| 2.3181 | 3.0 | 307 | 2.3030 | 0.9825 |
| 2.1968 | 4.0 | 410 | 1.9821 | 0.9555 |
| 1.7187 | 5.0 | 512 | 1.6775 | 0.9242 |
| 1.6233 | 6.0 | 615 | 1.6232 | 0.9440 |
| 1.5713 | 7.0 | 717 | 1.5419 | 0.9139 |
| 1.4064 | 8.0 | 820 | 1.3078 | 0.8956 |
| 1.2103 | 9.0 | 922 | 1.1363 | 0.8763 |
| 0.898 | 10.0 | 1025 | 0.8109 | 0.8318 |
| 0.6426 | 11.0 | 1127 | 0.6708 | 0.5635 |
| 0.4305 | 12.0 | 1230 | 0.4225 | 0.2889 |
| 0.2961 | 13.0 | 1332 | 0.3487 | 0.1892 |
| 0.1856 | 14.0 | 1435 | 0.2493 | 0.1223 |
| 0.137 | 15.0 | 1537 | 0.2439 | 0.1198 |
| 0.1115 | 16.0 | 1640 | 0.2321 | 0.1196 |
| 0.0923 | 17.0 | 1742 | 0.2226 | 0.1145 |
| 0.0796 | 18.0 | 1845 | 0.2115 | 0.1120 |
| 0.0742 | 19.0 | 1947 | 0.2082 | 0.1078 |
| 0.0684 | 19.9 | 2040 | 0.2053 | 0.1078 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Oct 30, 2023
- Updated
- Nov 3, 2023