|
--- |
|
language: |
|
- ml |
|
license: apache-2.0 |
|
tags: |
|
- whisper-event |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Tiny ml - Bharat Ramanathan |
|
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: ml |
|
split: test |
|
metrics: |
|
- type: wer |
|
value: 45.72 |
|
name: WER |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: google/fleurs |
|
type: google/fleurs |
|
config: ml_in |
|
split: test |
|
metrics: |
|
- type: wer |
|
value: 62.15 |
|
name: WER |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# Whisper Tiny ml - Bharat Ramanathan |
|
|
|
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.1286 |
|
- Wer: 106.9296 |
|
|
|
## 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 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 64 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- training_steps: 5000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.5755 | 4.02 | 500 | 0.4241 | 81.2652 | |
|
| 0.4182 | 9.01 | 1000 | 0.3245 | 72.7494 | |
|
| 0.3387 | 14.01 | 1500 | 0.2914 | 67.2749 | |
|
| 0.2923 | 19.0 | 2000 | 0.2745 | 60.3406 | |
|
| 0.2596 | 24.0 | 2500 | 0.2645 | 58.2725 | |
|
| 0.2356 | 28.02 | 3000 | 0.2629 | 60.3406 | |
|
| 0.2167 | 33.01 | 3500 | 0.2647 | 59.9757 | |
|
| 0.2039 | 4.02 | 4000 | 0.2617 | 58.2725 | |
|
| 0.1938 | 9.01 | 4500 | 0.2644 | 58.2725 | |
|
| 0.1858 | 14.01 | 5000 | 0.2636 | 58.7591 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.0.dev0 |
|
- Pytorch 1.13.0 |
|
- Datasets 2.7.1.dev0 |
|
- Tokenizers 0.13.2 |
|
|
