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---
language:
- ac
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- tericlabs
metrics:
- wer
model-index:
- name: Whisper base acholi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Sunbird
type: tericlabs
metrics:
- name: Wer
type: wer
value: 122.26379794200186
---
<!-- 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 acholi
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Sunbird dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8895
- Wer: 122.2638
## 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.2321 | 3.32 | 1000 | 2.9610 | 140.3181 |
| 2.5056 | 6.64 | 2000 | 2.7358 | 116.9317 |
| 2.0671 | 9.97 | 3000 | 2.7957 | 144.9953 |
| 1.7382 | 13.29 | 4000 | 2.8895 | 122.2638 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
|