transformers pytorch tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-base doi:10.57967/hf/1620 license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-atcosim
  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-atcosim

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0620
- Wer: 2.9820

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.152         | 8.33  | 500  | 0.0522          | 2.5282 |
| 0.001         | 16.67 | 1000 | 0.0539          | 3.0608 |
| 0.0003        | 25.0  | 1500 | 0.0556          | 3.0237 |
| 0.0002        | 33.33 | 2000 | 0.0567          | 3.0237 |
| 0.0001        | 41.67 | 2500 | 0.0579          | 3.0144 |
| 0.0001        | 50.0  | 3000 | 0.0588          | 2.9959 |
| 0.0001        | 58.33 | 3500 | 0.0597          | 3.0052 |
| 0.0001        | 66.67 | 4000 | 0.0604          | 3.0098 |
| 0.0           | 75.0  | 4500 | 0.0610          | 2.9867 |
| 0.0           | 83.33 | 5000 | 0.0615          | 2.9867 |
| 0.0           | 91.67 | 5500 | 0.0619          | 2.9774 |
| 0.0           | 100.0 | 6000 | 0.0620          | 2.9820 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.0
