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---
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-15hrs-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: swagen
type: swagen
metrics:
- name: Wer
type: wer
value: 0.27171266233766234
---
<!-- 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-15hrs-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: 0.4103
- Wer: 0.2717
## 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 |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 2.6268 | 0.1654 | 200 | 0.8031 | 0.4605 |
| 2.0712 | 0.3308 | 400 | 0.6148 | 0.3829 |
| 1.7302 | 0.4962 | 600 | 0.5562 | 0.3490 |
| 1.5735 | 0.6616 | 800 | 0.5103 | 0.3106 |
| 1.5623 | 0.8270 | 1000 | 0.4683 | 0.2776 |
| 1.2713 | 0.9924 | 1200 | 0.4439 | 0.2688 |
| 0.7209 | 1.1571 | 1400 | 0.4601 | 0.2732 |
| 0.6856 | 1.3225 | 1600 | 0.4391 | 0.2595 |
| 0.7661 | 1.4879 | 1800 | 0.4396 | 0.2755 |
| 0.8113 | 1.6533 | 2000 | 0.4262 | 0.2643 |
| 0.77 | 1.8187 | 2200 | 0.4175 | 0.2679 |
| 0.6942 | 1.9841 | 2400 | 0.4103 | 0.2717 |
| 0.2814 | 2.1489 | 2600 | 0.4295 | 0.2617 |
| 0.3171 | 2.3142 | 2800 | 0.4301 | 0.2432 |
| 0.3495 | 2.4796 | 3000 | 0.4299 | 0.2526 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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