metadata
license: apache-2.0
tags:
- generated_from_trainer
- whisper-event
metrics:
- wer
model-index:
- name: whisper-medium-et-ERR2020
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0
type: mozilla-foundation/common_voice_11_0
config: et
split: test
metrics:
- type: wer
value: 20.05
name: WER
whisper-medium-et-ERR2020
This model is a fine-tuned version of openai/whisper-medium on the following training sets: Common Voice 11, VoxPopuli, FLEURS and ERR2020. The checkpoint-7000 was on Whisper Event leaderboard. Current score is for the final checkpoint.
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: 32
- eval_batch_size: 16
- 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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1828 | 0.1 | 1000 | 0.3547 | 20.8829 |
| 0.09 | 0.2 | 2000 | 0.3476 | 19.0096 |
| 0.083 | 0.3 | 3000 | 0.3386 | 18.1304 |
| 0.0765 | 0.4 | 4000 | 0.3365 | 17.2591 |
| 0.0592 | 0.5 | 5000 | 0.3534 | 19.0213 |
| 0.0672 | 0.6 | 6000 | 0.3622 | 18.4263 |
| 0.0629 | 0.7 | 7000 | 0.3487 | 15.9839 |
| 0.0546 | 1.03 | 8000 | 0.3677 | 16.1021 |
| 0.0459 | 1.13 | 9000 | 0.3704 | 17.9073 |
| 0.0425 | 1.23 | 10000 | 0.3672 | 15.9119 |
The validation set is combined from the validation sets of Common Voice 11, VoxPopuli, FLEURS and ERR2020.
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+rocm5.1.1h
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2