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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: UDA-LIDI-Whisper-large-v3-ECU-911
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. -->
# UDA-LIDI-Whisper-large-v3-ECU-911
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8777
- Wer: 37.9051
## 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: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.6583 | 1.0 | 91 | 0.5713 | 39.8617 |
| 0.3725 | 2.0 | 182 | 0.5667 | 37.7866 |
| 0.2317 | 3.0 | 273 | 0.6098 | 37.6285 |
| 0.1397 | 4.0 | 364 | 0.6432 | 37.1937 |
| 0.0841 | 5.0 | 455 | 0.7177 | 39.4466 |
| 0.0539 | 6.0 | 546 | 0.7817 | 39.1700 |
| 0.036 | 7.0 | 637 | 0.8725 | 38.7747 |
| 0.0281 | 8.0 | 728 | 0.8485 | 39.6245 |
| 0.0228 | 9.0 | 819 | 0.8553 | 37.9051 |
| 0.0181 | 9.8950 | 900 | 0.8777 | 37.9051 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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