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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium.en
results: []
---
<!-- 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.en
This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on an [acc_dataset_v3](https://huggingface.co/datasets/monadical-labs/acc_dataset_v3) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4242
- Wer: 0.1293
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
See the training notebook [here](https://huggingface.co/monadical-labs/whisper-medium.en/blob/main/Finetuning-notebook-whisper-on-acc-data.ipynb):
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 4
- 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: 25
- training_steps: 300
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 1.6045 | 2.2727 | 25 | 0.9047 | 0.1535 |
| 0.2267 | 4.5455 | 50 | 0.4149 | 0.1262 |
| 0.0207 | 6.8182 | 75 | 0.4454 | 0.1483 |
| 0.0134 | 9.0909 | 100 | 0.4660 | 0.1388 |
| 0.009 | 11.3636 | 125 | 0.4311 | 0.1462 |
| 0.0051 | 13.6364 | 150 | 0.4368 | 0.1356 |
| 0.0018 | 15.9091 | 175 | 0.4294 | 0.1462 |
| 0.0003 | 18.1818 | 200 | 0.4234 | 0.1356 |
| 0.0002 | 20.4545 | 225 | 0.4235 | 0.1325 |
| 0.0002 | 22.7273 | 250 | 0.4239 | 0.1304 |
| 0.0002 | 25.0 | 275 | 0.4240 | 0.1283 |
| 0.0002 | 27.2727 | 300 | 0.4242 | 0.1293 |
### Framework versions
- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|