metadata
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- luigisaetta/atco2_normalized_augmented
metrics:
- wer
model-index:
- name: whisper-atco2-medium
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: luigisaetta/atco2_normalized_augmented
type: luigisaetta/atco2_normalized_augmented
config: en
split: test
metrics:
- name: Wer
type: wer
value: 17.50524109014675
whisper-atco2-medium
This model is a fine-tuned version of openai/whisper-medium on the luigisaetta/atco2_normalized_augmented dataset. It achieves the following results on the evaluation set:
- Loss: 0.6129
- Wer: 17.5052
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: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.3939 | 1.06 | 50 | 1.8493 | 66.5618 |
| 0.5127 | 2.13 | 100 | 0.5119 | 30.6080 |
| 0.0626 | 3.19 | 150 | 0.5410 | 20.4403 |
| 0.0157 | 4.25 | 200 | 0.5775 | 19.8113 |
| 0.0107 | 5.32 | 250 | 0.5552 | 19.7065 |
| 0.0044 | 6.38 | 300 | 0.5723 | 18.1342 |
| 0.0013 | 7.45 | 350 | 0.5763 | 17.7149 |
| 0.0005 | 8.51 | 400 | 0.6053 | 17.7149 |
| 0.0004 | 9.57 | 450 | 0.6109 | 17.5052 |
| 0.0004 | 10.64 | 500 | 0.6129 | 17.5052 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.11.0