File size: 2,469 Bytes
87ab066 7f2ab14 87ab066 7f2ab14 87ab066 7f2ab14 87ab066 7f2ab14 87ab066 41ead27 87ab066 7f2ab14 87ab066 41ead27 7f2ab14 41ead27 87ab066 7f2ab14 87ab066 7f2ab14 87ab066 7f2ab14 87ab066 |
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 90 91 92 |
---
language:
- el
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Greek - Robust
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 el
type: mozilla-foundation/common_voice_11_0
config: el
split: test
args: el
metrics:
- type: wer
value: 24.52637444279346
name: Wer
- type: wer
value: 20.42
name: WER
---
<!-- 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 Greek - Robust
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 el dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3605
- Wer: 24.5264
## 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-05
- train_batch_size: 16
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2223 | 2.35 | 500 | 0.4403 | 37.9922 |
| 0.0908 | 4.69 | 1000 | 0.4041 | 35.6519 |
| 0.0465 | 7.04 | 1500 | 0.4189 | 34.3053 |
| 0.0168 | 9.39 | 2000 | 0.3972 | 29.9127 |
| 0.0118 | 11.74 | 2500 | 0.4043 | 28.9933 |
| 0.0053 | 14.08 | 3000 | 0.3968 | 28.5940 |
| 0.0032 | 16.43 | 3500 | 0.3664 | 25.6779 |
| 0.0009 | 18.78 | 4000 | 0.3665 | 26.2444 |
| 0.0003 | 21.13 | 4500 | 0.3620 | 25.2879 |
| 0.0004 | 23.47 | 5000 | 0.3570 | 24.8607 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
|