transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer he base_model:openai/whisper-medium-ori endpoints_compatible region:us
---
language:
- he
base_model: openai/whisper-medium-ori
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: he
  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. -->

# he

This model is a fine-tuned version of [openai/whisper-medium-ori](https://huggingface.co/openai/whisper-medium-ori) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0478
- Wer: 7.1707

## 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: 4e-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
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.3738        | 0.02  | 50   | 0.1757          | 6.6641  |
| 0.1077        | 0.03  | 100  | 0.1403          | 33.0086 |
| 0.1118        | 0.05  | 150  | 0.1070          | 40.2962 |
| 0.0848        | 0.07  | 200  | 0.1144          | 16.7966 |
| 0.0879        | 0.08  | 250  | 0.1032          | 21.4341 |
| 0.0786        | 0.1   | 300  | 0.0971          | 7.0538  |
| 0.0665        | 0.11  | 350  | 0.0940          | 15.3157 |
| 0.0631        | 0.13  | 400  | 0.0868          | 14.6142 |
| 0.0591        | 0.15  | 450  | 0.0965          | 27.0460 |
| 0.0574        | 0.16  | 500  | 0.0807          | 19.0959 |
| 0.0536        | 0.18  | 550  | 0.0804          | 12.4318 |
| 0.0443        | 0.2   | 600  | 0.0791          | 3.9751  |
| 0.0455        | 0.21  | 650  | 0.0881          | 12.9774 |
| 0.0435        | 0.23  | 700  | 0.0772          | 6.0016  |
| 0.0439        | 0.25  | 750  | 0.0750          | 13.9906 |
| 0.0317        | 0.26  | 800  | 0.0645          | 9.4310  |
| 0.0352        | 0.28  | 850  | 0.0664          | 5.9626  |
| 0.0328        | 0.29  | 900  | 0.0633          | 8.4178  |
| 0.0287        | 0.31  | 950  | 0.0658          | 15.5105 |
| 0.0266        | 0.33  | 1000 | 0.0570          | 10.2494 |
| 0.0209        | 0.34  | 1050 | 0.0613          | 7.4825  |
| 0.0272        | 0.36  | 1100 | 0.0599          | 6.8589  |
| 0.024         | 0.38  | 1150 | 0.0583          | 10.8730 |
| 0.0203        | 0.39  | 1200 | 0.0538          | 8.0670  |
| 0.0187        | 0.41  | 1250 | 0.0508          | 5.4949  |
| 0.0165        | 0.43  | 1300 | 0.0507          | 6.8200  |
| 0.0106        | 0.44  | 1350 | 0.0504          | 7.3266  |
| 0.0203        | 0.46  | 1400 | 0.0477          | 7.7163  |
| 0.0142        | 0.48  | 1450 | 0.0480          | 7.5994  |
| 0.0194        | 0.49  | 1500 | 0.0478          | 7.1707  |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.0
