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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- bigcgen
metrics:
- wer
model-index:
- name: whisper-medium-bigcgen-male-5hrs-62
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: bigcgen
type: bigcgen
metrics:
- name: Wer
type: wer
value: 0.516229862947824
---
<!-- 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-bigcgen-male-5hrs-62
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the bigcgen dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6629
- Wer: 0.5162
## 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: 62
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.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
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.956 | 0.6211 | 200 | 0.8871 | 0.6444 |
| 0.6779 | 1.2422 | 400 | 0.7327 | 0.5585 |
| 0.5879 | 1.8634 | 600 | 0.6629 | 0.5162 |
| 0.4268 | 2.4845 | 800 | 0.6734 | 0.5006 |
| 0.1979 | 3.1056 | 1000 | 0.7147 | 0.4766 |
| 0.2338 | 3.7267 | 1200 | 0.7034 | 0.4869 |
| 0.1014 | 4.3478 | 1400 | 0.7554 | 0.4879 |
### Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0
|