whisper-NST-cons2e5 / README.md
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---
license: apache-2.0
tags:
- hf-asr-leaderboard
- automatic-speech-recognition
- NbAiLab/NST
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-NST-cons2e5
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-NST-cons2e5
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the NBAILAB/NST - NO-CLOSE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3521
- Wer: 11.8586
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2517 | 0.1 | 1000 | 0.4131 | 18.4721 |
| 0.1931 | 0.2 | 2000 | 0.3531 | 19.0422 |
| 0.1598 | 0.3 | 3000 | 0.3605 | 16.8757 |
| 0.1541 | 0.4 | 4000 | 0.3367 | 14.4812 |
| 0.1443 | 0.5 | 5000 | 0.3274 | 13.3409 |
| 0.1301 | 0.6 | 6000 | 0.3481 | 10.7184 |
| 0.1266 | 0.7 | 7000 | 0.3452 | 12.9989 |
| 0.1216 | 0.8 | 8000 | 0.3215 | 10.8324 |
| 0.1121 | 0.9 | 9000 | 0.3160 | 11.5165 |
| 0.1171 | 1.0 | 10000 | 0.3521 | 11.8586 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.13.1