File size: 2,639 Bytes
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license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-basque
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-base-basque
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2498
- Wer: 62.1644
## 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: 192
- eval_batch_size: 96
- 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: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4078 | 0.25 | 500 | 0.5613 | 136.6055 |
| 0.2533 | 0.5 | 1000 | 0.3973 | 105.6700 |
| 0.1994 | 0.74 | 1500 | 0.3350 | 73.1485 |
| 0.1723 | 0.99 | 2000 | 0.3101 | 55.7387 |
| 0.1403 | 1.24 | 2500 | 0.2895 | 49.8689 |
| 0.1318 | 1.49 | 3000 | 0.2800 | 70.4321 |
| 0.1279 | 1.73 | 3500 | 0.2711 | 80.4296 |
| 0.1192 | 1.98 | 4000 | 0.2667 | 60.5533 |
| 0.104 | 2.23 | 4500 | 0.2605 | 54.0402 |
| 0.0986 | 2.48 | 5000 | 0.2601 | 53.4158 |
| 0.0929 | 2.73 | 5500 | 0.2539 | 61.0653 |
| 0.0971 | 2.97 | 6000 | 0.2521 | 45.2104 |
| 0.0806 | 3.22 | 6500 | 0.2526 | 51.5736 |
| 0.0812 | 3.47 | 7000 | 0.2509 | 53.9903 |
| 0.0817 | 3.72 | 7500 | 0.2498 | 56.8440 |
| 0.0799 | 3.96 | 8000 | 0.2511 | 65.1305 |
| 0.0723 | 4.21 | 8500 | 0.2500 | 55.6326 |
| 0.0724 | 4.46 | 9000 | 0.2498 | 60.2910 |
| 0.0707 | 4.71 | 9500 | 0.2501 | 59.5854 |
| 0.0685 | 4.96 | 10000 | 0.2498 | 62.1644 |
### Framework versions
- Transformers 4.38.0
- Pytorch 2.1.1+cu121
- Datasets 2.8.0
- Tokenizers 0.15.2
|