---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- swagen
metrics:
- wer
model-index:
- name: whisper-medium-swagen-combined-30hrs-model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: swagen
      type: swagen
    metrics:
    - name: Wer
      type: wer
      value: 0.2234172077922078
---

<!-- 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-swagen-combined-30hrs-model

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the swagen dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3610
- Wer: 0.2234

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 500
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 2.7508        | 0.0828 | 200  | 0.8134          | 0.4877 |
| 1.8748        | 0.1656 | 400  | 0.6291          | 0.3898 |
| 1.6214        | 0.2484 | 600  | 0.5560          | 0.3431 |
| 1.559         | 0.3312 | 800  | 0.4968          | 0.2953 |
| 1.3616        | 0.4140 | 1000 | 0.4720          | 0.2872 |
| 1.3078        | 0.4967 | 1200 | 0.4577          | 0.2978 |
| 1.2579        | 0.5795 | 1400 | 0.4218          | 0.2758 |
| 1.214         | 0.6623 | 1600 | 0.4156          | 0.2654 |
| 1.0719        | 0.7451 | 1800 | 0.4005          | 0.2315 |
| 1.0432        | 0.8279 | 2000 | 0.3864          | 0.2433 |
| 0.9825        | 0.9107 | 2200 | 0.3743          | 0.2207 |
| 1.0952        | 0.9935 | 2400 | 0.3610          | 0.2234 |
| 0.6001        | 1.0766 | 2600 | 0.3888          | 0.2423 |
| 0.5491        | 1.1594 | 2800 | 0.3730          | 0.2265 |
| 0.6732        | 1.2422 | 3000 | 0.3702          | 0.2201 |


### Framework versions

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