metadata
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: []
he
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0736
- Precision: 0.4148
- Recall: 0.4107
- F1: 0.4125
- Precision Median: 0.0
- Recall Median: 0.0
- F1 Median: 0.0
- Precision Max: 1.0
- Recall Max: 1.0
- F1 Max: 1.0
- 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
- training_steps: 4000
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0445 | 0.4 | 1000 | 0.0839 | 0.2598 | 0.2539 | 0.2566 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 0.0203 | 0.79 | 2000 | 0.0686 | 0.5017 | 0.4976 | 0.4993 | 0.6667 | 0.6667 | 0.6667 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 0.013 | 1.19 | 3000 | 0.0723 | 0.3647 | 0.3629 | 0.3635 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
| 0.0016 | 1.58 | 4000 | 0.0736 | 0.4148 | 0.4107 | 0.4125 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 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