metadata
license: apache-2.0
datasets:
- Chillarmo/common_voice_20_armenian
language:
- hy
base_model:
- openai/whisper-base
pipeline_tag: automatic-speech-recognition
library_name: transformers
model-index:
- name: whisper-base-armenian
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 20 Armenian
type: Chillarmo/common_voice_20_armenian
metrics:
- type: wer
value: 33.186880780299205
name: Word Error Rate
- type: cer
value: 6.983058800639766
name: Character Error Rate
- type: bleu
value: 47.70616594276946
name: BLEU Score
- type: exact_match
value: 16.49590163934426
name: Exact Match
Whisper-Base Fine-tuned for Armenian ASR
This model is a fine-tuned version of OpenAI's Whisper-base on the Common Voice 20 Armenian dataset for automatic speech recognition.
Training Results
The model was trained for 5.34 epochs with the following final results:
| Metric | Value |
|---|---|
| Training Loss | 0.122 |
| Training Runtime | 10,924 seconds (≈3.03 hours) |
| Training Samples/Second | 7.32 |
| Training Steps/Second | 0.46 |
| Total Training Steps | 5,000 |
| Epochs | 5.34 |
Evaluation Results
| Metric | Value |
|---|---|
| Evaluation Loss | 0.201 |
| Word Error Rate (WER) | 33.19% |
| Character Error Rate (CER) | 6.98% |
| BLEU Score | 47.71 |
| Exact Match | 16.50% |
| Average Prediction Length | 7.69 tokens |
| Average Label Length | 7.77 tokens |
| Length Ratio | 0.989 |
| Evaluation Runtime | 1,590 seconds (≈26.5 minutes) |
| Evaluation Samples/Second | 3.68 |
| Evaluation Steps/Second | 0.46 |
Model Details
- Base Model: openai/whisper-base
- Language: Armenian (hy)
- Dataset: Chillarmo/common_voice_20_armenian
- License: Apache 2.0
Notes
During model loading, there were missing keys in the checkpoint: ['proj_out.weight']. This is a common occurrence when fine-tuning Whisper models and typically doesn't affect performance significantly.