---
base_model: openai/whisper-medium
datasets:
- generator
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: whisper-medium-sb-lug-eng-v2
  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-medium-sb-lug-eng-v2

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1255
- Wer Lug: 0.124
- Wer Eng: 0.171
- Wer Mean: 0.147
- Cer Lug: 0.028
- Cer Eng: 0.164
- Cer Mean: 0.096

## 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 Lug | Wer Eng | Wer Mean | Cer Lug | Cer Eng | Cer Mean |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:--------:|:-------:|:-------:|:--------:|
| 0.7222        | 0.1   | 500  | 0.2662          | 0.391   | 0.146   | 0.268    | 0.085   | 0.104   | 0.095    |
| 0.5452        | 0.2   | 1000 | 0.1894          | 0.223   | 0.058   | 0.141    | 0.05    | 0.034   | 0.042    |
| 0.4172        | 0.3   | 1500 | 0.1764          | 0.199   | 0.276   | 0.238    | 0.043   | 0.269   | 0.156    |
| 0.3949        | 0.4   | 2000 | 0.1583          | 0.177   | 0.035   | 0.106    | 0.039   | 0.017   | 0.028    |
| 0.3626        | 0.5   | 2500 | 0.1508          | 0.153   | 0.157   | 0.155    | 0.035   | 0.122   | 0.078    |
| 0.3467        | 0.6   | 3000 | 0.1397          | 0.14    | 0.258   | 0.199    | 0.033   | 0.213   | 0.123    |
| 0.3443        | 0.7   | 3500 | 0.1333          | 0.139   | 0.044   | 0.092    | 0.032   | 0.027   | 0.029    |
| 0.3169        | 0.8   | 4000 | 0.1297          | 0.129   | 0.027   | 0.078    | 0.029   | 0.011   | 0.02     |
| 0.3276        | 0.9   | 4500 | 0.1264          | 0.124   | 0.086   | 0.105    | 0.028   | 0.058   | 0.043    |
| 0.317         | 1.0   | 5000 | 0.1255          | 0.124   | 0.171   | 0.147    | 0.028   | 0.164   | 0.096    |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1