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---
language:
- fi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Finnish all
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 fi
type: mozilla-foundation/common_voice_11_0
config: fi
split: test
args: fi
metrics:
- name: Wer
type: wer
value: 25.43330821401658
---
<!-- 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 Small Finnish all
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 fi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5334
- Wer: 25.4333
## Model description
The Model is fine-tuned for 5000 steps/updates on CV11 Finnish train+valiation data.
- Zero-shot - 30.5 (CV9 test data, even on CV11 the WER is closer a bit higher than this)
- Fine-tuned - 25.43 (CV11 test data)
## 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: 64
- eval_batch_size: 32
- 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0025 | 19.0 | 1000 | 0.4265 | 24.8493 |
| 0.0005 | 38.0 | 2000 | 0.4785 | 25.3203 |
| 0.0003 | 57.01 | 3000 | 0.5073 | 25.3956 |
| 0.0002 | 76.01 | 4000 | 0.5253 | 25.4333 |
| 0.0002 | 96.0 | 5000 | 0.5334 | 25.4333 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|