---
library_name: transformers
language:
- lv
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper medium LV - Felikss Kleins
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: lv
      split: None
      args: 'config: lv, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 11.938731026829945
---

<!-- 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 medium LV - Felikss Kleins

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2416
- Wer: 11.9387

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| No log        | 0.02    | 200  | 0.2930          | 22.3576 |
| 0.9797        | 1.0116  | 400  | 0.2359          | 18.2083 |
| 0.357         | 2.0033  | 600  | 0.2274          | 16.4665 |
| 0.2582        | 2.0233  | 800  | 0.2111          | 15.6402 |
| 0.1718        | 3.0149  | 1000 | 0.2135          | 14.9883 |
| 0.1718        | 4.0066  | 1200 | 0.2090          | 14.2294 |
| 0.1355        | 4.0266  | 1400 | 0.2193          | 13.5537 |
| 0.1024        | 5.0183  | 1600 | 0.2255          | 14.5048 |
| 0.0836        | 6.0099  | 1800 | 0.2145          | 12.9751 |
| 0.0699        | 7.0015  | 2000 | 0.2232          | 13.2129 |
| 0.0699        | 7.0216  | 2200 | 0.2181          | 12.7155 |
| 0.0598        | 8.0132  | 2400 | 0.2192          | 12.7076 |
| 0.054         | 9.0048  | 2600 | 0.2348          | 13.0048 |
| 0.0452        | 9.0249  | 2800 | 0.2241          | 13.0940 |
| 0.0433        | 10.0165 | 3000 | 0.2406          | 12.6362 |
| 0.0433        | 11.0082 | 3200 | 0.2283          | 12.5332 |
| 0.0377        | 11.0282 | 3400 | 0.2293          | 12.2201 |
| 0.0317        | 12.0198 | 3600 | 0.2323          | 12.6144 |
| 0.0297        | 13.0114 | 3800 | 0.2309          | 12.2974 |
| 0.0267        | 14.0031 | 4000 | 0.2342          | 11.9011 |
| 0.0267        | 14.0231 | 4200 | 0.2286          | 12.1171 |
| 0.0243        | 15.0147 | 4400 | 0.2364          | 12.0854 |
| 0.0218        | 16.0064 | 4600 | 0.2405          | 12.1805 |
| 0.021         | 16.0264 | 4800 | 0.2422          | 12.0338 |
| 0.0173        | 17.0180 | 5000 | 0.2416          | 11.9387 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.0.1
- Datasets 3.0.0
- Tokenizers 0.19.1