|
--- |
|
language: |
|
- el |
|
license: apache-2.0 |
|
tags: |
|
- whisper-event |
|
- generated_from_trainer |
|
- hf-asr-leaderboard |
|
datasets: |
|
- mozilla-foundation/common_voice_11_0 |
|
- google/fleurs |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Medium El Greco |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 11.0 |
|
type: mozilla-foundation/common_voice_11_0 |
|
config: el |
|
split: test |
|
args: el |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 13.976597325408619 |
|
--- |
|
|
|
<!-- 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 El - Greek One |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4707 |
|
- Wer: 13.9766 |
|
|
|
## 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: 20 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.0036 | 10.01 | 1000 | 0.4461 | 15.9082 | |
|
| 0.0001 | 20.02 | 2000 | 0.4250 | 14.5245 | |
|
| 0.0 | 31.0 | 3000 | 0.4526 | 14.1902 | |
|
| 0.0 | 41.01 | 4000 | 0.4657 | 14.1252 | |
|
| 0.0 | 52.0 | 5000 | 0.4707 | 13.9766 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.0.dev0 |
|
- Pytorch 1.13.0+cu117 |
|
- Datasets 2.7.1.dev0 |
|
- Tokenizers 0.13.2 |