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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_F04
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_F04
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: 0.3499
- Wer: 26.6553
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.6368 | 0.85 | 500 | 0.3637 | 28.9474 |
| 0.11 | 1.69 | 1000 | 0.3521 | 36.5025 |
| 0.0969 | 2.54 | 1500 | 0.2911 | 46.3497 |
| 0.0679 | 3.39 | 2000 | 0.2895 | 27.0798 |
| 0.053 | 4.24 | 2500 | 0.3115 | 26.9949 |
| 0.0361 | 5.08 | 3000 | 0.2972 | 28.8625 |
| 0.0278 | 5.93 | 3500 | 0.3036 | 26.9100 |
| 0.0233 | 6.78 | 4000 | 0.3311 | 59.0832 |
| 0.0148 | 7.63 | 4500 | 0.3000 | 27.6740 |
| 0.0149 | 8.47 | 5000 | 0.3317 | 37.6061 |
| 0.0105 | 9.32 | 5500 | 0.2975 | 29.4567 |
| 0.0087 | 10.17 | 6000 | 0.3593 | 27.1647 |
| 0.0075 | 11.02 | 6500 | 0.2840 | 28.0985 |
| 0.004 | 11.86 | 7000 | 0.3760 | 26.7402 |
| 0.0039 | 12.71 | 7500 | 0.3477 | 33.4465 |
| 0.0029 | 13.56 | 8000 | 0.3595 | 26.0611 |
| 0.0022 | 14.41 | 8500 | 0.3429 | 29.5416 |
| 0.0013 | 15.25 | 9000 | 0.2967 | 24.0238 |
| 0.0004 | 16.1 | 9500 | 0.3539 | 28.4380 |
| 0.0003 | 16.95 | 10000 | 0.3646 | 25.1273 |
| 0.0001 | 17.8 | 10500 | 0.3638 | 25.4669 |
| 0.0001 | 18.64 | 11000 | 0.3502 | 26.3158 |
| 0.0001 | 19.49 | 11500 | 0.3499 | 26.6553 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.13.3
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