|
--- |
|
license: apache-2.0 |
|
tags: |
|
- hf-asr-leaderboard |
|
- automatic-speech-recognition |
|
- NbAiLab/NST |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: whisper-medium-NST-uf-linlr |
|
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. --> |
|
|
|
# whisper-medium-NST-uf-linlr |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the NBAILAB/NST - NO-CLOSE dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3007 |
|
- Wer: 9.1220 |
|
|
|
## 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: 72 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 1000 |
|
- training_steps: 20000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:| |
|
| 0.2046 | 0.05 | 1000 | 0.3426 | 15.2794 | |
|
| 0.148 | 0.1 | 2000 | 0.3284 | 10.8324 | |
|
| 0.121 | 0.15 | 3000 | 0.3092 | 12.8848 | |
|
| 0.1089 | 0.2 | 4000 | 0.2808 | 10.4903 | |
|
| 0.0976 | 0.25 | 5000 | 0.2617 | 9.9202 | |
|
| 0.0901 | 0.3 | 6000 | 0.2604 | 21.8928 | |
|
| 0.0834 | 0.35 | 7000 | 0.2877 | 9.3501 | |
|
| 0.0825 | 0.4 | 8000 | 0.2794 | 9.3501 | |
|
| 0.0553 | 1.05 | 9000 | 0.2845 | 9.5781 | |
|
| 0.0472 | 1.1 | 10000 | 0.2814 | 24.1733 | |
|
| 0.0409 | 1.15 | 11000 | 0.3084 | 8.0958 | |
|
| 0.041 | 1.2 | 12000 | 0.2865 | 9.2360 | |
|
| 0.0353 | 1.25 | 13000 | 0.2828 | 6.4994 | |
|
| 0.0348 | 1.3 | 14000 | 0.2708 | 7.5257 | |
|
| 0.0349 | 1.35 | 15000 | 0.2842 | 23.0331 | |
|
| 0.0361 | 1.4 | 16000 | 0.2769 | 10.1482 | |
|
| 0.0249 | 2.04 | 17000 | 0.2935 | 8.8940 | |
|
| 0.0204 | 2.09 | 18000 | 0.2874 | 12.4287 | |
|
| 0.0175 | 2.14 | 19000 | 0.2882 | 12.9989 | |
|
| 0.0197 | 2.19 | 20000 | 0.3007 | 9.1220 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.0.dev0 |
|
- Pytorch 1.13.0+cu117 |
|
- Datasets 2.6.1 |
|
- Tokenizers 0.13.1 |
|
|
