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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- bsbigcgen
metrics:
- wer
model-index:
- name: whisper-medium-bsbigcgen-female-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: bsbigcgen
type: bsbigcgen
metrics:
- name: Wer
type: wer
value: 0.47723480333730633
---
<!-- 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-bsbigcgen-female-model
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the bsbigcgen dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6368
- Wer: 0.4772
## 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 |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 3.47 | 0.6163 | 200 | 0.9274 | 0.6675 |
| 2.569 | 1.2311 | 400 | 0.7236 | 0.5511 |
| 2.5305 | 1.8475 | 600 | 0.6368 | 0.4772 |
| 1.4563 | 2.4622 | 800 | 0.6518 | 0.4937 |
| 0.6413 | 3.0770 | 1000 | 0.6892 | 0.4782 |
| 0.581 | 3.6934 | 1200 | 0.6935 | 0.4751 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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