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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- alxfng/noisycommonvoice
metrics:
- wer
model-index:
- name: Whisper Base Noisy
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Noisy Common Voice
type: alxfng/noisycommonvoice
config: en
split: None
metrics:
- name: Wer
type: wer
value: 59.32123598390824
---
<!-- 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 Noisy
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Noisy Common Voice dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4454
- Wer: 59.3212
## 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: 500
- training_steps: 4000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3125 | 3.19 | 1000 | 1.0918 | 56.8476 |
| 0.0585 | 6.39 | 2000 | 1.2650 | 58.9703 |
| 0.0153 | 9.58 | 3000 | 1.3946 | 58.3412 |
| 0.0066 | 12.78 | 4000 | 1.4454 | 59.3212 |
### Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
|