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# 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: 0.6841
- Wer: 78.8889

## 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: 2e-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: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0317        | 0.0   | 50   | 0.6685          | 84.4444 |
| 0.025         | 0.01  | 100  | 0.6933          | 78.8889 |
| 0.028         | 0.01  | 150  | 0.6201          | 84.4444 |
| 0.0255        | 0.02  | 200  | 0.6435          | 83.3333 |
| 0.0261        | 0.02  | 250  | 0.6456          | 81.1111 |
| 0.0282        | 0.02  | 300  | 0.6085          | 80.0    |
| 0.0232        | 0.03  | 350  | 0.6419          | 87.7778 |
| 0.0231        | 0.03  | 400  | 0.6923          | 84.4444 |
| 0.0194        | 0.04  | 450  | 0.6502          | 81.1111 |
| 0.0171        | 0.04  | 500  | 0.5778          | 80.0    |
| 0.0186        | 0.04  | 550  | 0.5946          | 76.6667 |
| 0.0185        | 0.05  | 600  | 0.5397          | 77.7778 |
| 0.0162        | 0.05  | 650  | 0.5710          | 78.8889 |
| 0.0166        | 0.06  | 700  | 0.5657          | 81.1111 |
| 0.0197        | 0.06  | 750  | 0.5782          | 78.8889 |
| 0.0169        | 0.06  | 800  | 0.6233          | 78.8889 |
| 0.0186        | 0.07  | 850  | 0.6032          | 81.1111 |
| 0.0135        | 0.07  | 900  | 0.5937          | 78.8889 |
| 0.0189        | 0.08  | 950  | 0.5835          | 83.3333 |
| 0.0179        | 0.08  | 1000 | 0.5586          | 81.1111 |
| 0.0153        | 0.08  | 1050 | 0.5648          | 77.7778 |
| 0.0153        | 0.09  | 1100 | 0.5614          | 75.5556 |
| 0.0132        | 0.09  | 1150 | 0.6051          | 83.3333 |
| 0.0149        | 0.1   | 1200 | 0.6085          | 83.3333 |
| 0.013         | 0.1   | 1250 | 0.5994          | 77.7778 |
| 0.0121        | 0.1   | 1300 | 0.6453          | 78.8889 |
| 0.0119        | 0.11  | 1350 | 0.6175          | 80.0    |
| 0.0099        | 0.11  | 1400 | 0.6126          | 76.6667 |
| 0.0102        | 0.12  | 1450 | 0.5911          | 74.4444 |
| 0.0096        | 0.12  | 1500 | 0.5650          | 74.4444 |
| 0.011         | 0.12  | 1550 | 0.5982          | 75.5556 |
| 0.0103        | 0.13  | 1600 | 0.6306          | 77.7778 |
| 0.009         | 0.13  | 1650 | 0.6372          | 76.6667 |
| 0.0067        | 0.14  | 1700 | 0.6389          | 80.0    |
| 0.0087        | 0.14  | 1750 | 0.6239          | 84.4444 |
| 0.0122        | 0.14  | 1800 | 0.6378          | 84.4444 |
| 0.0111        | 0.15  | 1850 | 0.6358          | 77.7778 |
| 0.008         | 0.15  | 1900 | 0.6517          | 82.2222 |
| 0.0066        | 0.16  | 1950 | 0.6067          | 74.4444 |
| 0.0071        | 0.16  | 2000 | 0.6129          | 72.2222 |
| 0.0085        | 0.16  | 2050 | 0.6240          | 73.3333 |
| 0.0063        | 0.17  | 2100 | 0.6302          | 72.2222 |
| 0.0067        | 0.17  | 2150 | 0.6266          | 73.3333 |
| 0.0056        | 0.18  | 2200 | 0.6297          | 77.7778 |
| 0.006         | 0.18  | 2250 | 0.6242          | 72.2222 |
| 0.0058        | 0.18  | 2300 | 0.6330          | 73.3333 |
| 0.0056        | 0.19  | 2350 | 0.6341          | 74.4444 |
| 0.0047        | 0.19  | 2400 | 0.6436          | 80.0    |
| 0.004         | 0.2   | 2450 | 0.6476          | 75.5556 |
| 0.0042        | 0.2   | 2500 | 0.6472          | 75.5556 |
| 0.0059        | 0.2   | 2550 | 0.6565          | 80.0    |
| 0.0045        | 0.21  | 2600 | 0.6565          | 80.0    |
| 0.0051        | 0.21  | 2650 | 0.6573          | 78.8889 |
| 0.0055        | 0.22  | 2700 | 0.6637          | 75.5556 |
| 0.0044        | 0.22  | 2750 | 0.6697          | 78.8889 |
| 0.0041        | 0.22  | 2800 | 0.6861          | 80.0    |
| 0.0054        | 0.23  | 2850 | 0.6839          | 78.8889 |
| 0.0033        | 0.23  | 2900 | 0.6859          | 78.8889 |
| 0.0041        | 0.24  | 2950 | 0.6841          | 78.8889 |
| 0.0027        | 0.24  | 3000 | 0.6841          | 78.8889 |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.13.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0

{"language": ["he"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-medium", "model-index": [{"name": "he", "results": []}]}
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