|
--- |
|
language: |
|
- es |
|
license: apache-2.0 |
|
tags: |
|
- hf-asr-leaderboard |
|
- generated_from_trainer |
|
datasets: |
|
- facebook/multilingual_librispeech |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Small Es - Sanchit Gandhi |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Multilingual LibriSpeech |
|
type: facebook/multilingual_librispeech |
|
args: 'config: es, split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 4.037333755183674 |
|
--- |
|
|
|
<!-- 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 Small Es - Sanchit Gandhi |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Multilingual LibriSpeech dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1035 |
|
- Wer: 4.0373 |
|
|
|
## 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: 4 |
|
- 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: 500 |
|
- training_steps: 4000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 0.1947 | 0.25 | 1000 | 0.1390 | 5.8261 | |
|
| 0.1226 | 0.5 | 2000 | 0.1224 | 4.9978 | |
|
| 0.1629 | 0.75 | 3000 | 0.1185 | 4.6543 | |
|
| 0.1916 | 1.0 | 4000 | 0.1035 | 4.0373 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.0.dev0 |
|
- Pytorch 1.12.0 |
|
- Datasets 2.6.2.dev0 |
|
- Tokenizers 0.12.1 |
|
|
