transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer dataset:google/fleurs base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small Tagalog
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs fil_ph
      type: google/fleurs
      config: fil_ph
      split: test
      args: fil_ph
    metrics:
    - name: Wer
      type: wer
      value: 20.66525391659729
---

<!-- 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 Tagalog

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs fil_ph dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6250
- Wer: 20.6653

## 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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0759        | 76.0  | 1000  | 0.5043          | 22.2622 |
| 0.0099        | 153.0 | 2000  | 0.5464          | 21.3653 |
| 0.0043        | 230.0 | 3000  | 0.5707          | 21.2215 |
| 0.0024        | 307.0 | 4000  | 0.5909          | 20.9377 |
| 0.0015        | 384.0 | 5000  | 0.6090          | 20.6728 |
| 0.001         | 461.0 | 6000  | 0.6250          | 20.6653 |
| 0.0007        | 538.0 | 7000  | 0.6395          | 20.8582 |
| 0.0005        | 615.0 | 8000  | 0.6519          | 20.9415 |
| 0.0004        | 692.0 | 9000  | 0.6613          | 20.9112 |
| 0.0004        | 769.0 | 10000 | 0.6653          | 20.9377 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
