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---
language:
- lv
license: apache-2.0
base_model: arturslogins/whisper-medium-lv
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- ta-dataset/training
metrics:
- wer
model-index:
- name: Whisper medium LV - Arturs Logins
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Recorded Voice
type: ta-dataset/training
config: lv
split: test
args: 'config: lv, split: test'
metrics:
- name: Wer
type: wer
value: 44.06162804804076
---
<!-- 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 - Arturs Logins
This model is a fine-tuned version of [arturslogins/whisper-medium-lv](https://huggingface.co/arturslogins/whisper-medium-lv) on the Recorded Voice dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1246
- Wer: 44.0616
## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0175 | 6.4 | 1000 | 0.9442 | 45.7358 |
| 0.0043 | 12.8 | 2000 | 0.9789 | 45.6994 |
| 0.0012 | 19.2 | 3000 | 1.0763 | 47.4221 |
| 0.0001 | 25.6 | 4000 | 1.1194 | 44.1708 |
| 0.0001 | 32.0 | 5000 | 1.1246 | 44.0616 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.0.1
- Datasets 2.19.0
- Tokenizers 0.19.1
|