---
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.