transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer hi dataset:mozilla-foundation/common_voice_11_Albanian base_model:openai/whisper-large-v2 license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- hi
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_Albanian
metrics:
- wer
model-index:
- name: Whisper large-v2 Albanian Test
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16 Albanian
      type: mozilla-foundation/common_voice_11_Albanian
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 34.05295315682281
---

<!-- 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 large-v2 Test

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 16 Albanian dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7073
- Wer: 34.0530

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1135        | 4.63  | 500  | 0.6519          | 44.8880 |
| 0.02          | 9.26  | 1000 | 0.6575          | 39.3483 |
| 0.0075        | 13.89 | 1500 | 0.6073          | 35.6823 |
| 0.0016        | 18.52 | 2000 | 0.6347          | 34.9084 |
| 0.0008        | 23.15 | 2500 | 0.6484          | 34.9491 |
| 0.0001        | 27.78 | 3000 | 0.6765          | 34.4196 |
| 0.0001        | 32.41 | 3500 | 0.6897          | 33.9308 |
| 0.0001        | 37.04 | 4000 | 0.6988          | 34.1752 |
| 0.0001        | 41.67 | 4500 | 0.7048          | 33.9715 |
| 0.0001        | 46.3  | 5000 | 0.7073          | 34.0530 |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
