---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- deepinfinityai/30_NLEM_Aug_audios_dataset
metrics:
- wer
model-index:
- name: v03_Med_30_NLEM_Aug_Tablets_Model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: /30_NLEM_Aug_audios_dataset
      type: deepinfinityai/30_NLEM_Aug_audios_dataset
    metrics:
    - name: Wer
      type: wer
      value: 0.0
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# v03_Med_30_NLEM_Aug_Tablets_Model

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the /30_NLEM_Aug_audios_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Wer: 0.0

## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- training_steps: 218
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0899        | 1.0   | 44   | 0.0198          | 2.8571 |
| 0.0007        | 2.0   | 88   | 0.0001          | 0.0    |
| 0.0001        | 3.0   | 132  | 0.0001          | 0.0    |
| 0.0001        | 4.0   | 176  | 0.0001          | 0.0    |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0