metadata
base_model: openai/whisper-large-v3
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v3-genbed-f
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: BembaSpeech
type: BembaSpeech
config: en
split: test
metrics:
- type: wer
value: 21.76
name: WER
whisper-large-v3-genbed-f
This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4613
- Wer: 28.2294
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: 1.75e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4575 | 0.6605 | 250 | 0.5118 | 48.6061 |
| 0.3575 | 1.3210 | 500 | 0.4580 | 41.5408 |
| 0.3229 | 1.9815 | 750 | 0.3920 | 34.9542 |
| 0.1937 | 2.6420 | 1000 | 0.4103 | 33.1986 |
| 0.0955 | 3.3025 | 1250 | 0.4218 | 32.8368 |
| 0.0943 | 3.9630 | 1500 | 0.4120 | 31.6982 |
| 0.0346 | 4.6235 | 1750 | 0.4397 | 30.2724 |
| 0.0123 | 5.2840 | 2000 | 0.4604 | 28.8891 |
| 0.0132 | 5.9445 | 2250 | 0.4485 | 29.1658 |
| 0.0025 | 6.6050 | 2500 | 0.4613 | 28.2294 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1