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:
- 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: 0.1370
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Precision Median: 0.0
- Recall Median: 0.0
- F1 Median: 0.0
- Precision Max: 0
- Recall Max: 0
- F1 Max: 0
- Precision Min: 0
- Recall Min: 0
- F1 Min: 0

## 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: 1e-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: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Precision Median | Recall Median | F1 Median | Precision Max | Recall Max | F1 Max | Precision Min | Recall Min | F1 Min |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:----------------:|:-------------:|:---------:|:-------------:|:----------:|:------:|:-------------:|:----------:|:------:|
| 0.0675        | 0.4   | 1000 | 0.1219          | 0.0       | 0.0    | 0.0 | 0.0              | 0.0           | 0.0       | 0             | 0          | 0      | 0             | 0          | 0      |
| 0.0313        | 0.79  | 2000 | 0.1256          | 0.0       | 0.0    | 0.0 | 0.0              | 0.0           | 0.0       | 0             | 0          | 0      | 0             | 0          | 0      |
| 0.0262        | 1.19  | 3000 | 0.1282          | 0.0       | 0.0    | 0.0 | 0.0              | 0.0           | 0.0       | 0             | 0          | 0      | 0             | 0          | 0      |
| 0.0063        | 1.58  | 4000 | 0.1273          | 0.0       | 0.0    | 0.0 | 0.0              | 0.0           | 0.0       | 0             | 0          | 0      | 0             | 0          | 0      |
| 0.0073        | 1.98  | 5000 | 0.1299          | 0.0       | 0.0    | 0.0 | 0.0              | 0.0           | 0.0       | 0             | 0          | 0      | 0             | 0          | 0      |
| 0.0024        | 2.37  | 6000 | 0.1337          | 0.0       | 0.0    | 0.0 | 0.0              | 0.0           | 0.0       | 0             | 0          | 0      | 0             | 0          | 0      |
| 0.0014        | 2.77  | 7000 | 0.1375          | 0.0       | 0.0    | 0.0 | 0.0              | 0.0           | 0.0       | 0             | 0          | 0      | 0             | 0          | 0      |
| 0.0002        | 3.17  | 8000 | 0.1370          | 0.0       | 0.0    | 0.0 | 0.0              | 0.0           | 0.0       | 0             | 0          | 0      | 0             | 0          | 0      |


### Framework versions

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