metadata
base_model: mohammadsp99/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper-small-FullFinetuning-CV-train-test
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: fa
split: test
args: fa
metrics:
- name: Wer
type: wer
value: 93.93939393939394
language:
- fa
library_name: adapter-transformers
Whisper-small-FullFinetuning-CV-train-test
This model is a fine-tuned version of mohammadsp99/whisper-small on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4865
- Wer: 37.3 The evaluation was done after training
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.886 | 0.05 | 100 | 2.1958 | 101.5152 |
| 0.6142 | 0.1 | 200 | 2.2113 | 110.6061 |
| 0.5544 | 0.15 | 300 | 2.2247 | 215.1515 |
| 0.4809 | 0.2 | 400 | 1.8149 | 104.5455 |
| 0.393 | 0.25 | 500 | 1.8802 | 96.9697 |
| 0.4191 | 0.3 | 600 | 1.9056 | 107.5758 |
| 0.3515 | 0.35 | 700 | 1.9166 | 89.3939 |
| 0.2671 | 0.4 | 800 | 1.9010 | 86.3636 |
| 0.2763 | 0.45 | 900 | 1.8574 | 96.9697 |
| 0.2896 | 0.5 | 1000 | 1.8940 | 95.4545 |
| 0.2201 | 0.55 | 1100 | 1.6264 | 96.9697 |
| 0.1937 | 0.6 | 1200 | 1.8990 | 98.4848 |
| 0.1787 | 0.65 | 1300 | 1.7999 | 100.0 |
| 0.1138 | 0.7 | 1400 | 1.8118 | 96.9697 |
| 0.1759 | 0.75 | 1500 | 1.9026 | 93.9394 |
| 0.1276 | 0.8 | 1600 | 1.8715 | 195.4545 |
| 0.1437 | 0.85 | 1700 | 1.7353 | 92.4242 |
| 0.1593 | 1.02 | 1800 | 1.7307 | 95.4545 |
| 0.1617 | 1.07 | 1900 | 1.7732 | 96.9697 |
| 0.1737 | 1.12 | 2000 | 1.7646 | 93.9394 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3