File size: 2,479 Bytes
dc0480d f383cae dc0480d f383cae dc0480d f383cae dc0480d f383cae dc0480d f383cae dc0480d f383cae dc0480d f383cae dc0480d f383cae dc0480d f383cae dc0480d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 |
---
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 Medium Danish (Common Voice Corpus 11.0)
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 da
type: mozilla-foundation/common_voice_11_0
config: da
split: test
args: da
metrics:
- name: Wer
type: wer
value: 16.13361388742767
---
<!-- 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 Danish (Common Voice Corpus 11.0)
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 da dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5081
- Wer: 16.1336
## 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: 32
- eval_batch_size: 16
- 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: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0229 | 7.01 | 1000 | 0.4464 | 16.5124 |
| 0.0072 | 15.0 | 2000 | 0.5081 | 16.1336 |
| 0.0048 | 22.01 | 3000 | 0.5193 | 16.6597 |
| 0.0034 | 30.0 | 4000 | 0.5715 | 16.8964 |
| 0.0005 | 37.01 | 5000 | 0.5998 | 16.4440 |
| 0.0007 | 45.01 | 6000 | 0.5908 | 16.8017 |
| 0.0001 | 53.0 | 7000 | 0.6093 | 16.2336 |
| 0.0001 | 60.01 | 8000 | 0.6405 | 16.3335 |
| 0.0 | 68.0 | 9000 | 0.6524 | 16.2493 |
| 0.0 | 75.01 | 10000 | 0.6569 | 16.2283 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|