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: 0.1002
- Precision: 0.0339
- Recall: 0.0359
- F1: 0.0348
- Precision Median: 0.0
- Recall Median: 0.0
- F1 Median: 0.0
- Precision Max: 0.9231
- Recall Max: 1.0
- F1 Max: 0.9600
- Precision Min: 0.0
- Recall Min: 0.0
- F1 Min: 0.0

## 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
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:----------------:|:-------------:|:---------:|:-------------:|:----------:|:------:|:-------------:|:----------:|:------:|
| 0.2011        | 0.2   | 500  | 0.2334          | 0.0486    | 0.0506 | 0.0495 | 0.0              | 0.0           | 0.0       | 0.8947        | 0.9444     | 0.9189 | 0.0           | 0.0        | 0.0    |
| 0.0923        | 0.4   | 1000 | 0.1190          | 0.0946    | 0.1001 | 0.0972 | 0.0              | 0.0           | 0.0       | 0.9524        | 1.0        | 0.9756 | 0.0           | 0.0        | 0.0    |
| 0.033         | 0.59  | 1500 | 0.1151          | 0.0468    | 0.0491 | 0.0479 | 0.0              | 0.0           | 0.0       | 0.9375        | 1.0        | 0.9600 | 0.0           | 0.0        | 0.0    |
| 0.0323        | 0.79  | 2000 | 0.1002          | 0.0339    | 0.0359 | 0.0348 | 0.0              | 0.0           | 0.0       | 0.9231        | 1.0        | 0.9600 | 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
