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: 0.0459
- Wer: 6.3133

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.3741        | 0.02  | 50   | 0.1764          | 6.9369  |
| 0.1107        | 0.03  | 100  | 0.1279          | 9.7428  |
| 0.1096        | 0.05  | 150  | 0.1029          | 13.0164 |
| 0.0857        | 0.07  | 200  | 0.1132          | 11.8472 |
| 0.0899        | 0.08  | 250  | 0.0909          | 6.8589  |
| 0.0814        | 0.1   | 300  | 0.1001          | 6.9369  |
| 0.0652        | 0.11  | 350  | 0.0940          | 7.0148  |
| 0.0623        | 0.13  | 400  | 0.0956          | 9.4310  |
| 0.057         | 0.15  | 450  | 0.0896          | 12.5097 |
| 0.0581        | 0.16  | 500  | 0.0841          | 5.6508  |
| 0.0518        | 0.18  | 550  | 0.0842          | 6.3913  |
| 0.0453        | 0.2   | 600  | 0.0818          | 4.8714  |
| 0.0445        | 0.21  | 650  | 0.0820          | 7.4045  |
| 0.0439        | 0.23  | 700  | 0.0741          | 9.7038  |
| 0.0456        | 0.25  | 750  | 0.0702          | 22.1356 |
| 0.032         | 0.26  | 800  | 0.0703          | 8.1450  |
| 0.0362        | 0.28  | 850  | 0.0657          | 6.3133  |
| 0.0339        | 0.29  | 900  | 0.0613          | 6.7810  |
| 0.029         | 0.31  | 950  | 0.0617          | 7.3655  |
| 0.0285        | 0.33  | 1000 | 0.0558          | 6.6641  |
| 0.0207        | 0.34  | 1050 | 0.0570          | 6.3913  |
| 0.0286        | 0.36  | 1100 | 0.0557          | 4.7545  |
| 0.0241        | 0.38  | 1150 | 0.0539          | 5.9626  |
| 0.0198        | 0.39  | 1200 | 0.0498          | 5.4170  |
| 0.0189        | 0.41  | 1250 | 0.0480          | 3.3125  |
| 0.0162        | 0.43  | 1300 | 0.0483          | 5.4949  |
| 0.0111        | 0.44  | 1350 | 0.0484          | 5.7677  |
| 0.0201        | 0.46  | 1400 | 0.0465          | 5.6118  |
| 0.0124        | 0.48  | 1450 | 0.0462          | 6.2744  |
| 0.0214        | 0.49  | 1500 | 0.0459          | 6.3133  |


### Framework versions

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