---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-ml-exp2
  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-ml-exp2

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: 0.2220
- Wer: 57.6922

## 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: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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
- training_steps: 15000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.3119        | 0.0333 | 500   | 0.4193          | 79.0917 |
| 0.0405        | 0.0667 | 1000  | 0.4335          | 73.5830 |
| 0.0355        | 0.1    | 1500  | 0.4332          | 77.2785 |
| 0.126         | 0.1333 | 2000  | 0.1967          | 58.4021 |
| 0.0519        | 0.1667 | 2500  | 0.1861          | 58.5671 |
| 0.0439        | 0.2    | 3000  | 0.1942          | 57.4274 |
| 0.0534        | 1.0112 | 3500  | 0.1936          | 61.1497 |
| 0.0214        | 1.0445 | 4000  | 0.2253          | 59.7816 |
| 0.0129        | 1.0779 | 4500  | 0.2630          | 61.0614 |
| 0.048         | 1.1112 | 5000  | 0.1780          | 56.3606 |
| 0.047         | 1.1445 | 5500  | 0.1638          | 52.9951 |
| 0.0325        | 1.1779 | 6000  | 0.1683          | 54.5512 |
| 0.0293        | 1.2112 | 6500  | 0.1689          | 57.2451 |
| 0.028         | 2.0224 | 7000  | 0.2145          | 56.5237 |
| 0.009         | 2.0557 | 7500  | 0.2227          | 56.3068 |
| 0.0076        | 2.0891 | 8000  | 0.2750          | 66.0540 |
| 0.0385        | 2.1224 | 8500  | 0.2178          | 54.4514 |
| 0.0245        | 2.1557 | 9000  | 0.1721          | 52.0031 |
| 0.0226        | 2.1891 | 9500  | 0.1741          | 53.7511 |
| 0.0212        | 3.0003 | 10000 | 0.2001          | 56.1495 |
| 0.0121        | 3.0336 | 10500 | 0.2322          | 55.4722 |
| 0.0042        | 3.0669 | 11000 | 0.2403          | 57.6864 |
| 0.0059        | 3.1003 | 11500 | 0.2953          | 64.0067 |
| 0.0248        | 3.1336 | 12000 | 0.1744          | 51.3412 |
| 0.0172        | 3.1669 | 12500 | 0.1872          | 53.5324 |
| 0.015         | 3.2003 | 13000 | 0.1930          | 54.7028 |
| 0.0158        | 4.0115 | 13500 | 0.2173          | 60.9636 |
| 0.0028        | 4.0448 | 14000 | 0.2330          | 53.4921 |
| 0.0028        | 4.0781 | 14500 | 0.2415          | 53.4767 |
| 0.0194        | 4.1115 | 15000 | 0.2220          | 57.6922 |


### Framework versions

- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1