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license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny-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-tiny-basque
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: 0.4296
- Wer: 28.7020
## 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: 256
- eval_batch_size: 128
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.7245 | 0.21 | 500 | 0.9431 | 64.8287 |
| 0.4752 | 0.42 | 1000 | 0.6923 | 48.8196 |
| 0.4115 | 0.63 | 1500 | 0.6084 | 40.8976 |
| 0.3696 | 0.84 | 2000 | 0.5597 | 37.1048 |
| 0.3336 | 1.05 | 2500 | 0.5289 | 36.0029 |
| 0.3189 | 1.26 | 3000 | 0.5082 | 33.5204 |
| 0.3007 | 1.47 | 3500 | 0.4903 | 32.4969 |
| 0.2935 | 1.68 | 4000 | 0.4802 | 31.6632 |
| 0.2839 | 1.89 | 4500 | 0.4695 | 30.7243 |
| 0.2594 | 2.1 | 5000 | 0.4615 | 30.2538 |
| 0.2507 | 2.31 | 5500 | 0.4547 | 29.4160 |
| 0.2574 | 2.52 | 6000 | 0.4487 | 29.5852 |
| 0.2523 | 2.73 | 6500 | 0.4429 | 28.5473 |
| 0.2471 | 2.94 | 7000 | 0.4393 | 29.3562 |
| 0.2329 | 3.15 | 7500 | 0.4373 | 29.2592 |
| 0.2346 | 3.36 | 8000 | 0.4343 | 28.5947 |
| 0.2322 | 3.57 | 8500 | 0.4332 | 29.0136 |
| 0.2304 | 3.78 | 9000 | 0.4305 | 28.1387 |
| 0.2299 | 3.99 | 9500 | 0.4300 | 28.0768 |
| 0.236 | 4.2 | 10000 | 0.4296 | 28.7020 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.1.1+cu121
- Datasets 2.8.0
- Tokenizers 0.15.2
|