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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-nomi
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-small-nomi
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.6383
## 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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 132
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.4305 | 1.9417 | 100 | 0.1954 | 36.8085 |
| 0.3179 | 3.8835 | 200 | 0.1760 | 71.7021 |
| 0.1876 | 5.8252 | 300 | 0.2092 | 24.4681 |
| 0.1377 | 7.7670 | 400 | 0.1063 | 23.1915 |
| 0.0933 | 9.7087 | 500 | 0.0556 | 7.8723 |
| 0.0713 | 11.6505 | 600 | 0.0556 | 9.5745 |
| 0.0548 | 13.5922 | 700 | 0.0289 | 5.1064 |
| 0.0436 | 15.5340 | 800 | 0.0330 | 3.6170 |
| 0.0258 | 17.4757 | 900 | 0.0041 | 0.8511 |
| 0.0094 | 19.4175 | 1000 | 0.0072 | 2.1277 |
| 0.0047 | 21.3592 | 1100 | 0.0001 | 1.7021 |
| 0.001 | 23.3010 | 1200 | 0.0001 | 0.8511 |
| 0.0 | 25.2427 | 1300 | 0.0000 | 0.6383 |
| 0.0 | 27.1845 | 1400 | 0.0000 | 0.6383 |
| 0.0 | 29.1262 | 1500 | 0.0000 | 0.6383 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
|