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---
language:
- da
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small da - Common Voice+FLEURS
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0, FLEURS
type: mozilla-foundation/common_voice_11_0
config: da
split: test
args: da
metrics:
- name: Wer
type: wer
value: 138.8532351394003
---
<!-- 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 da - Common Voice+FLEURS
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0, FLEURS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9242
- Wer: 138.8532
## 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-07
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.22 | 15.0 | 1000 | 1.2238 | 197.5434 |
| 1.004 | 30.0 | 2000 | 1.0386 | 197.9221 |
| 0.9104 | 45.01 | 3000 | 0.9704 | 156.6544 |
| 0.8455 | 60.01 | 4000 | 0.9352 | 142.3619 |
| 0.8237 | 75.01 | 5000 | 0.9242 | 138.8532 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2