Downloads · 30 days
2
1% of all-time downloads
Whisper-small-model-FullFinetuning-train-test
MohammadFazli/Whisper-small-model-FullFinetuning-train-test
Whisper-small-model-FullFinetuning-train-test is a automatic speech recognition model from MohammadFazli. 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
145
Public
Parameters
242M
9.7 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors967 MB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Jan 31, 2024
- Updated
- Jan 31, 2024
- SHA
- 3c4d1c50
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. -->
Whisper-small-model-FullFinetuning-train-test
This model is a fine-tuned version of openai/whisper-small on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.6703
- Wer: 96.9697
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.131 | 0.05 | 100 | 2.2796 | 100.0 |
| 0.6661 | 0.1 | 200 | 2.1839 | 96.9697 |
| 0.5889 | 0.15 | 300 | 2.1523 | 107.5758 |
| 0.5005 | 0.2 | 400 | 1.9232 | 107.5758 |
| 0.421 | 0.25 | 500 | 1.9957 | 101.5152 |
| 0.4363 | 0.3 | 600 | 1.9424 | 96.9697 |
| 0.3583 | 0.35 | 700 | 1.9280 | 95.4545 |
| 0.2703 | 0.4 | 800 | 2.0008 | 93.9394 |
| 0.2836 | 0.45 | 900 | 1.9656 | 90.9091 |
| 0.2948 | 0.5 | 1000 | 1.7947 | 100.0 |
| 0.2236 | 0.55 | 1100 | 1.5250 | 100.0 |
| 0.2029 | 0.6 | 1200 | 1.8172 | 95.4545 |
| 0.1811 | 0.65 | 1300 | 1.8721 | 90.9091 |
| 0.1186 | 0.7 | 1400 | 1.7841 | 96.9697 |
| 0.1765 | 0.75 | 1500 | 1.7462 | 95.4545 |
| 0.1328 | 0.8 | 1600 | 1.7392 | 100.0 |
| 0.1428 | 0.85 | 1700 | 1.7447 | 100.0 |
| 0.1634 | 1.02 | 1800 | 1.6684 | 90.9091 |
| 0.1678 | 1.07 | 1900 | 1.6602 | 101.5152 |
| 0.1826 | 1.12 | 2000 | 1.6703 | 96.9697 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Jan 31, 2024
- Updated
- Jan 31, 2024