---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large
tags:
- generated_from_trainer
datasets:
- deepinfinityai/30_report_sentences_dataset
metrics:
- wer
model-index:
- name: Whisper_Large_30_sent_Model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: 11 Sentences
      type: deepinfinityai/30_report_sentences_dataset
    metrics:
    - name: Wer
      type: wer
      value: 169.6969696969697
---

<!-- 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_Large_30_sent_Model

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the 11 Sentences dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8472
- Wer: 169.6970

## 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: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.3891        | 8.3333  | 50   | 1.2466          | 21.2121  |
| 0.0553        | 16.6667 | 100  | 0.1580          | 18.1818  |
| 0.0002        | 25.0    | 150  | 0.1879          | 157.5758 |
| 0.0002        | 33.3333 | 200  | 0.2462          | 87.8788  |
| 0.0001        | 41.6667 | 250  | 0.3595          | 200.0    |
| 0.0001        | 50.0    | 300  | 0.5265          | 190.9091 |
| 0.0001        | 58.3333 | 350  | 0.6597          | 184.8485 |
| 0.0001        | 66.6667 | 400  | 0.7327          | 175.7576 |
| 0.0001        | 75.0    | 450  | 0.8169          | 172.7273 |
| 0.0001        | 83.3333 | 500  | 0.8472          | 169.6970 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0