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---
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: 67.95180722891565
---
<!-- 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: 1.1313
- Wer: 67.9518
## 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-06
- train_batch_size: 6
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| No log | 23.0009 | 200 | 0.9920 | 47.2289 |
| 1.4829 | 47.0001 | 400 | 0.7982 | 48.9157 |
| 0.046 | 70.001 | 600 | 0.9576 | 51.3253 |
| 0.011 | 94.0002 | 800 | 0.9129 | 49.3976 |
| 0.0057 | 117.0011 | 1000 | 0.9789 | 51.3253 |
| 0.0057 | 141.0003 | 1200 | 1.0248 | 51.8072 |
| 0.005 | 164.0012 | 1400 | 1.0504 | 53.4940 |
| 0.0021 | 188.0004 | 1600 | 1.0447 | 67.9518 |
| 0.0015 | 211.0013 | 1800 | 1.0433 | 73.2530 |
| 0.0012 | 235.0005 | 2000 | 1.0646 | 55.1807 |
| 0.0012 | 258.0014 | 2200 | 1.1244 | 53.7349 |
| 0.0007 | 282.0006 | 2400 | 1.1156 | 59.5181 |
| 0.0006 | 305.0015 | 2600 | 1.1081 | 58.5542 |
| 0.0009 | 329.0007 | 2800 | 1.0342 | 54.4578 |
| 0.0006 | 352.0016 | 3000 | 1.0215 | 50.8434 |
| 0.0006 | 376.0008 | 3200 | 1.0619 | 56.6265 |
| 0.0004 | 399.0017 | 3400 | 1.1083 | 55.4217 |
| 0.0003 | 423.0009 | 3600 | 1.0970 | 56.8675 |
| 0.0006 | 447.0001 | 3800 | 1.1047 | 59.0361 |
| 0.0003 | 470.001 | 4000 | 1.1033 | 56.1446 |
| 0.0003 | 494.0002 | 4200 | 1.1003 | 57.5904 |
| 0.0002 | 517.0011 | 4400 | 1.1133 | 68.4337 |
| 0.0002 | 541.0003 | 4600 | 1.1146 | 69.3976 |
| 0.0001 | 564.0012 | 4800 | 1.1267 | 69.8795 |
| 0.0001 | 588.0004 | 5000 | 1.1313 | 67.9518 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.0.1
- Datasets 3.0.0
- Tokenizers 0.19.1
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