transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer he base_model:openai/whisper-medium license:apache-2.0 endpoints_compatible region:us
---
language:
- he
license: apache-2.0
base_model: openai/whisper-medium
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](https://huggingface.co/openai/whisper-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0111
- Wer: 37.4517

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0155        | 0.02  | 50   | 0.0160          | 82.2919 |
| 0.0191        | 0.04  | 100  | 0.0271          | 41.2986 |
| 0.0194        | 0.06  | 150  | 0.0244          | 40.1791 |
| 0.0179        | 0.07  | 200  | 0.0223          | 34.4189 |
| 0.0157        | 0.09  | 250  | 0.0259          | 25.5445 |
| 0.016         | 0.11  | 300  | 0.0248          | 33.1773 |
| 0.0139        | 0.13  | 350  | 0.0214          | 29.3914 |
| 0.02          | 0.15  | 400  | 0.0223          | 37.3092 |
| 0.0149        | 0.17  | 450  | 0.0243          | 55.5669 |
| 0.0147        | 0.18  | 500  | 0.0210          | 70.0997 |
| 0.0134        | 0.2   | 550  | 0.0303          | 69.6519 |
| 0.0122        | 0.22  | 600  | 0.0182          | 47.2420 |
| 0.0104        | 0.24  | 650  | 0.0213          | 32.7906 |
| 0.0114        | 0.26  | 700  | 0.0171          | 25.8091 |
| 0.01          | 0.28  | 750  | 0.0171          | 40.4641 |
| 0.0071        | 0.3   | 800  | 0.0157          | 45.0641 |
| 0.0069        | 0.31  | 850  | 0.0172          | 49.5217 |
| 0.008         | 0.33  | 900  | 0.0169          | 48.7075 |
| 0.0056        | 0.35  | 950  | 0.0158          | 42.0721 |
| 0.0074        | 0.37  | 1000 | 0.0141          | 37.8587 |
| 0.0056        | 0.39  | 1050 | 0.0143          | 30.9994 |
| 0.0057        | 0.41  | 1100 | 0.0140          | 37.8995 |
| 0.0052        | 0.42  | 1150 | 0.0136          | 36.7393 |
| 0.003         | 0.44  | 1200 | 0.0127          | 34.9685 |
| 0.0034        | 0.46  | 1250 | 0.0119          | 35.5994 |
| 0.0041        | 0.48  | 1300 | 0.0118          | 37.6756 |
| 0.005         | 0.5   | 1350 | 0.0113          | 38.1641 |
| 0.0037        | 0.52  | 1400 | 0.0110          | 38.4490 |
| 0.0021        | 0.54  | 1450 | 0.0111          | 37.4517 |
| 0.0023        | 0.55  | 1500 | 0.0111          | 37.4517 |


### Framework versions

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