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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper-squeezeformer-NSQU-whisper-sparse-A
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-squeezeformer-NSQU-whisper-sparse-A
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the LibriSpeech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1860
- Wer: 9.1296
## 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: 20
- 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: 3000
- training_steps: 36000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.89 | 1.0 | 3000 | 3.2878 | 114.5015 |
| 1.1579 | 2.0 | 6000 | 0.7947 | 42.0578 |
| 0.3888 | 3.0 | 9000 | 0.7379 | 36.9314 |
| 0.2242 | 4.0 | 12000 | 0.7417 | 35.9172 |
| 0.5221 | 5.0 | 15000 | 0.6811 | 32.7808 |
| 0.324 | 6.0 | 18000 | 0.6716 | 32.0457 |
| 0.2034 | 7.0 | 21000 | 0.6845 | 32.0073 |
| 0.2177 | 9.6 | 24000 | 0.1991 | 10.8624 |
| 0.127 | 10.8 | 27000 | 0.1856 | 10.5485 |
| 0.0909 | 12.0 | 30000 | 0.1838 | 9.5918 |
| 0.0785 | 13.2 | 33000 | 0.1849 | 9.1030 |
| 0.0595 | 14.4 | 36000 | 0.1860 | 9.1296 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0
|