transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-medium license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-ro
  results: []
---

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# whisper-medium-ro

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1812
- Wer: 99.5018

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0777        | 1.8   | 1000 | 0.1651          | 100.1685 |
| 0.024         | 3.6   | 2000 | 0.1634          | 99.8853  |
| 0.0039        | 5.4   | 3000 | 0.1734          | 99.5484  |
| 0.001         | 7.19  | 4000 | 0.1812          | 99.5018  |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.1
- Datasets 2.16.0
- Tokenizers 0.15.0
