metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-small-dv
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train
args: en-US
metrics:
- name: Wer
type: wer
value: 0.3010625737898465
whisper-small-dv
This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5722
- Wer Ortho: 0.3023
- Wer: 0.3011
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: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 2
- training_steps: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| No log | 0.0714 | 2 | 0.5676 | 0.3140 | 0.3158 |
| No log | 0.1429 | 4 | 0.5642 | 0.3054 | 0.3076 |
| No log | 0.2143 | 6 | 0.5657 | 0.3004 | 0.3017 |
| No log | 0.2857 | 8 | 0.5681 | 0.3023 | 0.3034 |
| No log | 0.3571 | 10 | 0.5722 | 0.3023 | 0.3011 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0+cpu
- Datasets 3.1.0
- Tokenizers 0.20.3