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library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-minds14-en
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
metrics:
- name: Wer
type: wer
value: 0.3317591499409681
---
<!-- 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-minds14-en
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5435
- Wer Ortho: 0.3455
- Wer: 0.3318
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 3.1062 | 0.4386 | 25 | 2.2016 | 0.5077 | 0.3955 |
| 1.3065 | 0.8772 | 50 | 0.5662 | 0.4183 | 0.3878 |
| 0.4383 | 1.3158 | 75 | 0.4933 | 0.3775 | 0.3613 |
| 0.4020 | 1.7544 | 100 | 0.4771 | 0.3578 | 0.3453 |
| 0.3583 | 2.1930 | 125 | 0.4733 | 0.3689 | 0.3571 |
| 0.2264 | 2.6316 | 150 | 0.4765 | 0.3689 | 0.3583 |
| 0.2011 | 3.0702 | 175 | 0.4696 | 0.3350 | 0.3235 |
| 0.1494 | 3.5088 | 200 | 0.4826 | 0.3387 | 0.3241 |
| 0.1448 | 3.9474 | 225 | 0.4852 | 0.3535 | 0.3394 |
| 0.0698 | 4.3860 | 250 | 0.4920 | 0.3251 | 0.3146 |
| 0.0871 | 4.8246 | 275 | 0.5013 | 0.3257 | 0.3140 |
| 0.0560 | 5.2632 | 300 | 0.5130 | 0.3331 | 0.3217 |
| 0.0414 | 5.7018 | 325 | 0.5216 | 0.3430 | 0.3323 |
| 0.0347 | 6.1404 | 350 | 0.5242 | 0.3362 | 0.3247 |
| 0.0205 | 6.5789 | 375 | 0.5344 | 0.3313 | 0.3205 |
| 0.0259 | 7.0175 | 400 | 0.5328 | 0.3436 | 0.3335 |
| 0.0122 | 7.4561 | 425 | 0.5374 | 0.3467 | 0.3365 |
| 0.0213 | 7.8947 | 450 | 0.5417 | 0.3455 | 0.3329 |
| 0.0102 | 8.3333 | 475 | 0.5428 | 0.3424 | 0.3282 |
| 0.0111 | 8.7719 | 500 | 0.5435 | 0.3455 | 0.3318 |
### Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
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