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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: whisper-training-blog
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fleurs
type: fleurs
config: sv_se
split: validation
args: sv_se
metrics:
- name: Wer
type: wer
value: 191.23423279578478
---
<!-- 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-training-blog
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0050
- Wer: 191.2342
## 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: 7.5e-06
- 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_ratio: 0.3
- training_steps: 448
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4111 | 0.1 | 44 | 1.4919 | 245.3457 |
| 1.0501 | 0.2 | 88 | 1.2255 | 225.8822 |
| 0.9032 | 0.29 | 132 | 1.1203 | 211.6558 |
| 0.8141 | 1.06 | 176 | 1.0675 | 184.6240 |
| 0.8029 | 1.16 | 220 | 1.0394 | 178.4129 |
| 0.6325 | 1.25 | 264 | 1.0301 | 216.6374 |
| 0.6971 | 2.02 | 308 | 1.0135 | 184.4004 |
| 0.6051 | 2.12 | 352 | 1.0065 | 194.7150 |
| 0.6047 | 2.21 | 396 | 1.0029 | 166.9328 |
| 0.585 | 2.31 | 440 | 1.0050 | 191.2342 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
|