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---
language:
- es
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- Mezosky/es_clinical_assistance_10k
metrics:
- wer
model-index:
- name: Whisper Chilean Spanish Large v3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Mezosky/es_clinical_assistance_10k
type: Mezosky/es_clinical_assistance_10k
metrics:
- name: Wer
type: wer
value: 6.935235697300322
---
<!-- 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 Chilean Spanish Large v3
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the Mezosky/es_clinical_assistance_10k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0961
- Wer: 6.9352
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2816 | 0.17 | 100 | 0.2250 | 11.2827 |
| 0.1505 | 0.34 | 200 | 0.1479 | 9.8196 |
| 0.1293 | 0.51 | 300 | 0.1350 | 72.1192 |
| 0.1221 | 0.69 | 400 | 0.1292 | 9.6825 |
| 0.141 | 0.86 | 500 | 0.1194 | 53.0899 |
| 0.0922 | 1.03 | 600 | 0.1150 | 12.0380 |
| 0.0773 | 1.2 | 700 | 0.1079 | 12.8661 |
| 0.0745 | 1.37 | 800 | 0.1036 | 67.3017 |
| 0.0699 | 1.54 | 900 | 0.1016 | 8.2697 |
| 0.0917 | 1.72 | 1000 | 0.0956 | 8.6334 |
| 0.0716 | 1.89 | 1100 | 0.0968 | 7.7997 |
| 0.0441 | 2.06 | 1200 | 0.0946 | 8.3760 |
| 0.0377 | 2.23 | 1300 | 0.0963 | 7.6178 |
| 0.0417 | 2.4 | 1400 | 0.0951 | 7.5703 |
| 0.0409 | 2.57 | 1500 | 0.0926 | 7.2681 |
| 0.0356 | 2.74 | 1600 | 0.0912 | 6.8933 |
| 0.0361 | 2.92 | 1700 | 0.0918 | 7.0835 |
| 0.0215 | 3.09 | 1800 | 0.0938 | 6.9548 |
| 0.018 | 3.26 | 1900 | 0.0960 | 6.6415 |
| 0.0196 | 3.43 | 2000 | 0.0961 | 6.9352 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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