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---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny-final
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-tiny-final
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0714
- Wer: 6.3947
## Model description
Step Training Loss Validation Loss Wer
1000 0.727300 0.734777 71.347666
2000 0.392000 0.430395 52.059163
3000 0.317100 0.305939 39.781162
4000 0.206400 0.225029 30.785726
5000 0.152800 0.169434 23.076923
6000 0.119000 0.130408 16.517293
7000 0.082300 0.102279 11.755650
8000 0.079600 0.085155 8.511574
9000 0.051400 0.075068 7.048991
10000 0.045000 0.071429 6.394678
## 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: 16
- 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: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.7273 | 1.6051 | 1000 | 0.7348 | 71.3477 |
| 0.392 | 3.2103 | 2000 | 0.4304 | 52.0592 |
| 0.3171 | 4.8154 | 3000 | 0.3059 | 39.7812 |
| 0.2064 | 6.4205 | 4000 | 0.2250 | 30.7857 |
| 0.1528 | 8.0257 | 5000 | 0.1694 | 23.0769 |
| 0.119 | 9.6308 | 6000 | 0.1304 | 16.5173 |
| 0.0823 | 11.2360 | 7000 | 0.1023 | 11.7556 |
| 0.0796 | 12.8411 | 8000 | 0.0852 | 8.5116 |
| 0.0514 | 14.4462 | 9000 | 0.0751 | 7.0490 |
| 0.045 | 16.0514 | 10000 | 0.0714 | 6.3947 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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