metadata
language:
- eu
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Basque
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 eu
type: mozilla-foundation/common_voice_13_0
config: eu
split: test
args: eu
metrics:
- name: Wer
type: wer
value: 18.417108833893636
Whisper Small Basque
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_13_0 eu dataset. It achieves the following results on the evaluation set:
- Loss: 0.3390
- Wer: 18.4171
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: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2826 | 1.04 | 1000 | 0.3472 | 24.9342 |
| 0.0872 | 2.07 | 2000 | 0.3012 | 20.2661 |
| 0.0275 | 3.11 | 3000 | 0.3085 | 19.3021 |
| 0.0086 | 4.14 | 4000 | 0.3297 | 18.7513 |
| 0.0051 | 6.01 | 5000 | 0.3390 | 18.4171 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3