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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny-1000-diverse-audios
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-1000-diverse-audios
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1835
- Wer: 42.9577
## 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
- 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: 25
- training_steps: 500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 3.7684 | 0.4425 | 25 | 2.2485 | 135.5131 |
| 1.5347 | 0.8850 | 50 | 0.9286 | 75.5533 |
| 0.8425 | 1.3274 | 75 | 0.5561 | 56.4386 |
| 0.5722 | 1.7699 | 100 | 0.4103 | 43.4608 |
| 0.3867 | 2.2124 | 125 | 0.3423 | 40.5433 |
| 0.3107 | 2.6549 | 150 | 0.2967 | 51.0060 |
| 0.2931 | 3.0973 | 175 | 0.2656 | 78.8732 |
| 0.2031 | 3.5398 | 200 | 0.2421 | 57.8471 |
| 0.2004 | 3.9823 | 225 | 0.2305 | 51.8109 |
| 0.1254 | 4.4248 | 250 | 0.2198 | 22.4346 |
| 0.1332 | 4.8673 | 275 | 0.2070 | 22.2334 |
| 0.1089 | 5.3097 | 300 | 0.2049 | 51.4085 |
| 0.0627 | 5.7522 | 325 | 0.1988 | 28.5714 |
| 0.0959 | 6.1947 | 350 | 0.1948 | 31.6901 |
| 0.0794 | 6.6372 | 375 | 0.1910 | 28.8732 |
| 0.0696 | 7.0796 | 400 | 0.1879 | 43.5614 |
| 0.0458 | 7.5221 | 425 | 0.1861 | 43.4608 |
| 0.0524 | 7.9646 | 450 | 0.1841 | 53.5211 |
| 0.0453 | 8.4071 | 475 | 0.1832 | 40.4427 |
| 0.0485 | 8.8496 | 500 | 0.1835 | 42.9577 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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