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---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-google-fleurs-pt-br
results: []
---
<!-- 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-google-fleurs-pt-br
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6283
- Wer: 25.9071
## 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: 2.5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 120
- training_steps: 2400
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0871 | 2.72 | 400 | 0.4838 | 24.4078 |
| 0.0066 | 5.44 | 800 | 0.5647 | 25.5452 |
| 0.0013 | 8.16 | 1200 | 0.5981 | 25.6110 |
| 0.0008 | 10.88 | 1600 | 0.6143 | 25.6533 |
| 0.0006 | 13.61 | 2000 | 0.6245 | 25.7661 |
| 0.0006 | 16.33 | 2400 | 0.6283 | 25.9071 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1
- Datasets 2.16.1
- Tokenizers 0.15.0
|