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---
library_name: peft
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- wft
- whisper
- automatic-speech-recognition
- audio
- speech
- generated_from_trainer
datasets:
- hf-internal-testing/librispeech_asr_dummy
metrics:
- wer
model-index:
- name: wft-test-model
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: hf-internal-testing/librispeech_asr_dummy
type: hf-internal-testing/librispeech_asr_dummy
metrics:
- type: wer
value: 5.905511811023622
name: Wer
---
<!-- 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. -->
# wft-test-model
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the hf-internal-testing/librispeech_asr_dummy dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1185
- Wer: 5.9055
- Cer: 83.2386
- Decode Time: 0.5299
- Wer Time: 0.0047
- Cer Time: 0.0030
## 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: 0.0005
- train_batch_size: 4
- 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: 50
- training_steps: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Decode Time | Wer Time | Cer Time |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:--------:|:--------:|
| 2.4079 | 0.1 | 10 | 1.9885 | 312.2047 | 119.2472 | 0.5334 | 0.0169 | 0.0041 |
| 1.2303 | 1.01 | 20 | 1.1646 | 258.2677 | 100.0 | 0.5213 | 1.4057 | 0.0046 |
| 0.8667 | 1.11 | 30 | 0.8100 | 37.7953 | 52.3438 | 0.5008 | 0.0396 | 0.0045 |
| 0.4517 | 2.02 | 40 | 0.6337 | 40.9449 | 73.7926 | 0.5137 | 0.0217 | 0.0030 |
| 0.4352 | 2.12 | 50 | 0.4493 | 16.5354 | 88.1392 | 0.5203 | 0.0054 | 0.0032 |
| 0.2341 | 3.03 | 60 | 0.2922 | 8.2677 | 97.5852 | 0.5434 | 0.0060 | 0.0032 |
| 0.2233 | 3.13 | 70 | 0.2026 | 9.0551 | 83.5227 | 0.5359 | 0.0063 | 0.0033 |
| 0.1098 | 4.04 | 80 | 0.1665 | 5.9055 | 83.9489 | 0.5316 | 0.0056 | 0.0029 |
| 0.0678 | 4.14 | 90 | 0.1279 | 7.0866 | 81.1080 | 0.5388 | 0.0079 | 0.0038 |
| 0.078 | 5.05 | 100 | 0.1185 | 5.9055 | 83.2386 | 0.5299 | 0.0047 | 0.0030 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.5.0
- Datasets 3.0.2
- Tokenizers 0.20.1 |