---
language:
- he
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- precision
- recall
- f1
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: 0.0582
- Precision: 0.0005
- Recall: 0.0005
- F1: 0.0005

## 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.074         | 0.2   | 500  | 0.1027          | 0.0       | 0.0    | 0.0    |
| 0.0393        | 0.4   | 1000 | 0.0712          | 0.0       | 0.0    | 0.0    |
| 0.0161        | 0.59  | 1500 | 0.0597          | 0.0009    | 0.0009 | 0.0009 |
| 0.0114        | 0.79  | 2000 | 0.0582          | 0.0005    | 0.0005 | 0.0005 |


### Framework versions

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