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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-multiclass-lang-en-tiny
  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-multiclass-lang-en-tiny

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1349
- Wer: 7.7873
- Cer: 5.4535

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|
| 0.0661        | 4.5872  | 500  | 0.2294          | 11.3485 | 7.0165  |
| 0.0033        | 9.1743  | 1000 | 0.1563          | 17.7113 | 11.5596 |
| 0.0005        | 13.7615 | 1500 | 0.1456          | 8.0247  | 5.3246  |
| 0.0003        | 18.3486 | 2000 | 0.1414          | 7.8348  | 5.1271  |
| 0.0002        | 22.9358 | 2500 | 0.1390          | 8.5945  | 5.7798  |
| 0.0002        | 27.5229 | 3000 | 0.1374          | 8.5470  | 5.9258  |
| 0.0001        | 32.1101 | 3500 | 0.1362          | 7.9772  | 5.5136  |
| 0.0001        | 36.6972 | 4000 | 0.1355          | 7.8348  | 5.4449  |
| 0.0001        | 41.2844 | 4500 | 0.1351          | 7.7873  | 5.4449  |
| 0.0001        | 45.8716 | 5000 | 0.1349          | 7.7873  | 5.4535  |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0