transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer ate dataset:tericlabs base_model:openai/whisper-base license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- ate
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- tericlabs
metrics:
- wer
model-index:
- name: Whisper base ateso
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Sunbird
      type: tericlabs
    metrics:
    - name: Wer
      type: wer
      value: 27.710843373493976
---

<!-- 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 base ateso

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Sunbird dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5293
- Wer: 27.7108

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4597        | 3.5   | 1000 | 0.5186          | 32.1285 |
| 0.1812        | 6.99  | 2000 | 0.4394          | 26.7738 |
| 0.0429        | 10.49 | 3000 | 0.4765          | 26.7738 |
| 0.016         | 13.99 | 4000 | 0.5157          | 27.3092 |
| 0.0053        | 17.48 | 5000 | 0.5293          | 27.7108 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
