File size: 2,166 Bytes
fb8a9cb 88684e7 fb8a9cb 88684e7 fb8a9cb 88684e7 fb8a9cb 88684e7 fb8a9cb 8cb5e8c fb8a9cb 88684e7 fb8a9cb 8cb5e8c 88684e7 8cb5e8c fb8a9cb 88684e7 fb8a9cb 88684e7 fb8a9cb 88684e7 fb8a9cb |
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 |
---
language:
- cy
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Welsh - Robust
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 cy
type: mozilla-foundation/common_voice_11_0
config: cy
split: test
args: cy
metrics:
- type: wer
value: 23.073562122656497
name: Wer
- type: wer
value: 20.33
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 Welsh - 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 cy dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4569
- Wer: 23.0736
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0597 | 6.1 | 1000 | 0.4690 | 29.4666 |
| 0.0107 | 12.2 | 2000 | 0.4707 | 26.2671 |
| 0.0026 | 18.29 | 3000 | 0.4643 | 24.6763 |
| 0.0007 | 24.39 | 4000 | 0.4629 | 23.8024 |
| 0.0004 | 30.49 | 5000 | 0.4610 | 23.0616 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
|