transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer dataset:johnatanebonilla/coser base_model:openai/whisper-small doi:10.57967/hf/1559 license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-coser
  results: []
datasets:
- johnatanebonilla/coser
---

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# whisper-small-coser

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on [coser-asr](https://huggingface.co/johnatanebonilla/coser) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7951
- Wer: 108.2685

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8783        | 0.3   | 1000 | 0.9044          | 96.7315  |
| 0.7787        | 0.59  | 2000 | 0.8388          | 102.7047 |
| 0.7897        | 0.89  | 3000 | 0.8049          | 107.5558 |
| 0.6478        | 1.19  | 4000 | 0.7951          | 108.2685 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0