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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_M03_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_M03_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: 0.3051
- Wer: 41.5959
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.7806 | 0.85 | 500 | 0.2631 | 52.1222 |
| 0.0945 | 1.71 | 1000 | 0.2804 | 34.4652 |
| 0.071 | 2.56 | 1500 | 0.2464 | 22.5806 |
| 0.0455 | 3.41 | 2000 | 0.2476 | 21.3073 |
| 0.0335 | 4.27 | 2500 | 0.2581 | 21.2224 |
| 0.0253 | 5.12 | 3000 | 0.2617 | 25.0424 |
| 0.0177 | 5.97 | 3500 | 0.2898 | 26.4007 |
| 0.0127 | 6.83 | 4000 | 0.3068 | 24.5331 |
| 0.0111 | 7.68 | 4500 | 0.2925 | 41.9355 |
| 0.0087 | 8.53 | 5000 | 0.3179 | 23.2598 |
| 0.0064 | 9.39 | 5500 | 0.2884 | 29.8812 |
| 0.0056 | 10.24 | 6000 | 0.2952 | 35.4839 |
| 0.0037 | 11.09 | 6500 | 0.2956 | 26.4007 |
| 0.0035 | 11.95 | 7000 | 0.2839 | 27.3345 |
| 0.0028 | 12.8 | 7500 | 0.2975 | 28.3531 |
| 0.0019 | 13.65 | 8000 | 0.3129 | 42.3599 |
| 0.0018 | 14.51 | 8500 | 0.2932 | 31.5789 |
| 0.0015 | 15.36 | 9000 | 0.3047 | 32.0883 |
| 0.0008 | 16.21 | 9500 | 0.3071 | 37.4363 |
| 0.0008 | 17.06 | 10000 | 0.3081 | 39.8981 |
| 0.0006 | 17.92 | 10500 | 0.3064 | 39.5586 |
| 0.0003 | 18.77 | 11000 | 0.3052 | 40.2377 |
| 0.0002 | 19.62 | 11500 | 0.3051 | 41.5959 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.13.3
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