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---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_tiny_finetune_M04_frozen_encoder
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. -->
# torgo_tiny_finetune_M04_frozen_encoder
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: 0.2842
- Wer: 39.5586
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.7695 | 0.84 | 500 | 0.2502 | 52.2920 |
| 0.0895 | 1.69 | 1000 | 0.2592 | 39.9830 |
| 0.069 | 2.53 | 1500 | 0.2494 | 22.3260 |
| 0.0465 | 3.37 | 2000 | 0.2667 | 29.6265 |
| 0.0311 | 4.22 | 2500 | 0.2489 | 20.4584 |
| 0.0241 | 5.06 | 3000 | 0.2731 | 23.1749 |
| 0.0156 | 5.9 | 3500 | 0.2608 | 30.3056 |
| 0.0127 | 6.75 | 4000 | 0.2944 | 25.2971 |
| 0.0102 | 7.59 | 4500 | 0.2818 | 25.8913 |
| 0.008 | 8.43 | 5000 | 0.2610 | 25.1273 |
| 0.0079 | 9.27 | 5500 | 0.2632 | 24.6180 |
| 0.0054 | 10.12 | 6000 | 0.2776 | 29.4567 |
| 0.0047 | 10.96 | 6500 | 0.2758 | 28.0985 |
| 0.003 | 11.8 | 7000 | 0.2744 | 26.9949 |
| 0.0033 | 12.65 | 7500 | 0.2875 | 22.0713 |
| 0.0022 | 13.49 | 8000 | 0.2842 | 34.7199 |
| 0.0019 | 14.33 | 8500 | 0.2776 | 29.7963 |
| 0.0012 | 15.18 | 9000 | 0.2850 | 35.2292 |
| 0.0012 | 16.02 | 9500 | 0.2770 | 28.9474 |
| 0.0006 | 16.86 | 10000 | 0.2797 | 56.3667 |
| 0.0006 | 17.71 | 10500 | 0.2807 | 37.0119 |
| 0.0002 | 18.55 | 11000 | 0.2849 | 36.7572 |
| 0.0002 | 19.39 | 11500 | 0.2842 | 39.5586 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.13.3
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