---
license: apache-2.0
base_model: openai/whisper-large
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-r22-e
  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-r22-e

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2567
- Wer: 32.4317

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 150
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 4.2827        | 0.02  | 10   | 2.4594          | 30.6262 |
| 1.5383        | 0.04  | 20   | 0.9529          | 36.0561 |
| 0.5967        | 0.05  | 30   | 0.4230          | 34.7607 |
| 0.3559        | 0.07  | 40   | 0.3960          | 33.9352 |
| 0.314         | 0.09  | 50   | 0.3285          | 32.7270 |
| 0.3339        | 0.11  | 60   | 0.3362          | 33.3244 |
| 0.3148        | 0.13  | 70   | 0.2927          | 31.6464 |
| 0.3128        | 0.14  | 80   | 0.2896          | 32.5458 |
| 0.3136        | 0.16  | 90   | 0.2828          | 32.8613 |
| 0.272         | 0.18  | 100  | 0.2818          | 33.9419 |
| 0.1936        | 0.2   | 110  | 0.2702          | 30.9148 |
| 0.2541        | 0.22  | 120  | 0.2644          | 31.8209 |
| 0.2957        | 0.23  | 130  | 0.2614          | 31.6531 |
| 0.2867        | 0.25  | 140  | 0.2574          | 31.6397 |
| 0.2085        | 0.27  | 150  | 0.2567          | 32.4317 |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1