|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
base_model: openai/whisper-tiny |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- PolyAI/minds14 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Tiny finetuned on PolyAI Minds14 English US |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Speech Transcription in English from e-banking domain. |
|
type: PolyAI/minds14 |
|
config: en-US |
|
split: train |
|
args: en-US |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.3822590938098277 |
|
--- |
|
|
|
<!-- 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 Tiny finetuned on PolyAI Minds14 English US |
|
|
|
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Speech Transcription in English from e-banking domain. dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8668 |
|
- Wer Ortho: 0.4009 |
|
- Wer: 0.3823 |
|
|
|
## 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: 64 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: constant_with_warmup |
|
- lr_scheduler_warmup_steps: 50 |
|
- training_steps: 400 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
|
| 0.3501 | 3.57 | 100 | 0.7134 | 0.4568 | 0.4212 | |
|
| 0.044 | 7.14 | 200 | 0.7639 | 0.4096 | 0.3746 | |
|
| 0.0048 | 10.71 | 300 | 0.8265 | 0.4109 | 0.3854 | |
|
| 0.0021 | 14.29 | 400 | 0.8668 | 0.4009 | 0.3823 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.0 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.15.0 |
|
|
