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---
base_model: openai/whisper-medium
datasets:
- mozilla-foundation/common_voice_11_0
language:
- id
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: whisper-medium-id
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: id
split: test
args: 'config: id, split: test'
metrics:
- type: wer
value: 13.605283966696124
name: Wer
---
<!-- 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-medium-id
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2226
- Wer: 13.6053
## 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-06
- 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: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2022 | 1.9305 | 1000 | 0.1830 | 13.1308 |
| 0.1089 | 3.8610 | 2000 | 0.1824 | 13.0192 |
| 0.0609 | 5.7915 | 3000 | 0.1949 | 13.2657 |
| 0.0327 | 7.7220 | 4000 | 0.2125 | 13.4797 |
| 0.0257 | 9.6525 | 5000 | 0.2226 | 13.6053 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
|