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---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-cit-do0.15-wd0.0001
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-large-cit-do0.15-wd0.0001
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the SF 200 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6948
- Wer: 34.0961
## 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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- 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: 100
- training_steps: 200
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.1267 | 0.8889 | 10 | 1.1143 | 48.9703 |
| 1.0883 | 1.7778 | 20 | 1.0068 | 40.0458 |
| 0.9315 | 2.6667 | 30 | 0.8667 | 38.9016 |
| 0.751 | 3.5556 | 40 | 0.7886 | 34.0961 |
| 0.6968 | 4.4444 | 50 | 0.7158 | 35.0114 |
| 0.5946 | 5.3333 | 60 | 0.6504 | 31.8078 |
| 0.5011 | 6.2222 | 70 | 0.6133 | 31.3501 |
| 0.4061 | 7.1111 | 80 | 0.5869 | 33.6384 |
| 0.3731 | 8.0 | 90 | 0.5718 | 32.9519 |
| 0.2977 | 8.8889 | 100 | 0.5688 | 33.1808 |
| 0.2612 | 9.7778 | 110 | 0.5742 | 32.9519 |
| 0.2105 | 10.6667 | 120 | 0.5845 | 32.2654 |
| 0.1775 | 11.5556 | 130 | 0.5981 | 32.7231 |
| 0.1479 | 12.4444 | 140 | 0.6118 | 31.1213 |
| 0.1173 | 13.3333 | 150 | 0.6255 | 33.1808 |
| 0.111 | 14.2222 | 160 | 0.6426 | 35.4691 |
| 0.0946 | 15.1111 | 170 | 0.6641 | 34.5538 |
| 0.0799 | 16.0 | 180 | 0.6772 | 34.7826 |
| 0.0739 | 16.8889 | 190 | 0.6904 | 34.0961 |
| 0.0682 | 17.7778 | 200 | 0.6948 | 34.0961 |
### Framework versions
- Transformers 4.41.1
- Pytorch 1.13.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
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