File size: 2,123 Bytes
7681a59 0804027 7681a59 |
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 |
---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- divakaivan/glaswegian_audio
metrics:
- wer
model-index:
- name: Glaswegian_Whisper
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Glaswegian audio
type: divakaivan/glaswegian_audio
config: default
split: train
args: default
metrics:
- name: Wer
type: wer
value: 40.5394016013485
---
Fine-tuned using [this notebook](https://colab.research.google.com/drive/1CCRr0rXts18cios1zaIZv7SxhCub-gu-?usp=sharing)
<!-- 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. -->
# Glaswegian_Whisper
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Glaswegian audio dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4788
- Wer: 40.5394
## 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: 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0084 | 16.3934 | 1000 | 1.2802 | 38.5588 |
| 0.0019 | 32.7869 | 2000 | 1.4141 | 39.0223 |
| 0.0002 | 49.1803 | 3000 | 1.4553 | 40.3287 |
| 0.0001 | 65.5738 | 4000 | 1.4788 | 40.5394 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|