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---
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base.en-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.en-atcosim

This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0634
- Wer: 4.1443

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3402        | 8.33  | 500  | 0.0540          | 5.1398 |
| 0.0011        | 16.67 | 1000 | 0.0557          | 4.2693 |
| 0.0003        | 25.0  | 1500 | 0.0571          | 3.9128 |
| 0.0002        | 33.33 | 2000 | 0.0583          | 3.7553 |
| 0.0001        | 41.67 | 2500 | 0.0594          | 3.5840 |
| 0.0001        | 50.0  | 3000 | 0.0603          | 3.4729 |
| 0.0001        | 58.33 | 3500 | 0.0613          | 3.3571 |
| 0.0001        | 66.67 | 4000 | 0.0619          | 3.3108 |
| 0.0           | 75.0  | 4500 | 0.0625          | 4.2369 |
| 0.0           | 83.33 | 5000 | 0.0630          | 4.2184 |
| 0.0           | 91.67 | 5500 | 0.0633          | 4.1489 |
| 0.0           | 100.0 | 6000 | 0.0634          | 4.1443 |


### Framework versions

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