---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-reverse-ml-mft-1
  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-reverse-ml-mft-1

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0811
- Wer: 40.3159
- Cer: 12.1262

## 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: 0.0002
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 593
- training_steps: 5928

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.0582        | 1.0   | 1482 | 0.0768          | 43.4159 | 13.4134 |
| 0.0399        | 2.0   | 2964 | 0.0669          | 41.7880 | 12.4496 |
| 0.026         | 3.0   | 4446 | 0.0715          | 39.8821 | 11.8874 |
| 0.0169        | 4.0   | 5928 | 0.0811          | 40.3159 | 12.1262 |


### Framework versions

- Transformers 4.51.1
- Pytorch 2.8.0+cu128
- Datasets 4.4.1
- Tokenizers 0.21.4