|
--- |
|
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 |
|
|