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---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: whisper-large-v3-pt-cv16-cuda
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_0 pt
type: mozilla-foundation/common_voice_16_0
split: None
args: pt
metrics:
- name: Wer
type: wer
value: 0.9998545572074984
---
<!-- 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-large-v3-pt-cv16-cuda
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the mozilla-foundation/common_voice_16_0 pt dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1325
- Wer: 0.9999
## 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: 8
- 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: 2000
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.199 | 0.26 | 1000 | 0.1563 | 0.1124 |
| 0.1654 | 0.52 | 2000 | 0.1500 | 0.1052 |
| 0.1794 | 0.77 | 3000 | 0.1379 | 0.0997 |
| 0.0821 | 1.03 | 4000 | 0.1321 | 1.0007 |
| 0.1292 | 1.29 | 5000 | 0.1325 | 0.9999 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.2.0.dev20231212
- Datasets 2.15.1.dev0
- Tokenizers 0.15.0
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