metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-it-small-multids-augmented
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: it
split: test
args: it
metrics:
- name: Wer
type: wer
value: 8.749734212204975
whisper-it-small-multids-augmented
This model is a fine-tuned version of openai/whisper-small on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1978
- Wer: 8.7497
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 25000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1927 | 1.0 | 2500 | 0.2506 | 14.9991 |
| 0.0736 | 2.01 | 5000 | 0.2258 | 12.7864 |
| 0.0413 | 3.01 | 7500 | 0.2144 | 11.4508 |
| 0.0201 | 4.02 | 10000 | 0.2146 | 10.8774 |
| 0.0129 | 5.02 | 12500 | 0.2127 | 10.6920 |
| 0.0091 | 6.03 | 15000 | 0.2117 | 10.2867 |
| 0.0043 | 7.03 | 17500 | 0.2076 | 9.6860 |
| 0.0018 | 8.04 | 20000 | 0.2065 | 9.4235 |
| 0.0013 | 9.04 | 22500 | 0.2003 | 8.9105 |
| 0.0009 | 10.05 | 25000 | 0.1978 | 8.7497 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2