88 lines
2.3 KiB
Markdown
88 lines
2.3 KiB
Markdown
|
---
|
||
|
|
license: apache-2.0
|
||
|
|
base_model: openai/whisper-tiny
|
||
|
|
tags:
|
||
|
|
- whisper-event
|
||
|
|
- generated_from_trainer
|
||
|
|
datasets:
|
||
|
|
- common_voice_11_0
|
||
|
|
metrics:
|
||
|
|
- wer
|
||
|
|
model-index:
|
||
|
|
- name: WhisperTinyFinnishV3
|
||
|
|
results:
|
||
|
|
- task:
|
||
|
|
name: Automatic Speech Recognition
|
||
|
|
type: automatic-speech-recognition
|
||
|
|
dataset:
|
||
|
|
name: common_voice_11_0
|
||
|
|
type: common_voice_11_0
|
||
|
|
config: fi
|
||
|
|
split: test
|
||
|
|
args: fi
|
||
|
|
metrics:
|
||
|
|
- name: Wer
|
||
|
|
type: wer
|
||
|
|
value: 45.13758009800226
|
||
|
|
---
|
||
|
|
|
||
|
|
<!-- 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. -->
|
||
|
|
|
||
|
|
# WhisperTinyFinnishV3
|
||
|
|
|
||
|
|
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the common_voice_11_0 dataset.
|
||
|
|
It achieves the following results on the evaluation set:
|
||
|
|
- Loss: 0.5363
|
||
|
|
- Wer: 45.1376
|
||
|
|
|
||
|
|
## 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: 3e-06
|
||
|
|
- train_batch_size: 32
|
||
|
|
- eval_batch_size: 4
|
||
|
|
- seed: 42
|
||
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
||
|
|
- lr_scheduler_type: linear
|
||
|
|
- lr_scheduler_warmup_steps: 1000
|
||
|
|
- training_steps: 10000
|
||
|
|
- mixed_precision_training: Native AMP
|
||
|
|
|
||
|
|
### Training results
|
||
|
|
|
||
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer |
|
||
|
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
|
||
|
|
| 0.9236 | 0.1 | 1000 | 0.7783 | 58.5187 |
|
||
|
|
| 0.727 | 0.2 | 2000 | 0.6638 | 53.1097 |
|
||
|
|
| 0.6867 | 0.3 | 3000 | 0.6113 | 50.2639 |
|
||
|
|
| 0.8348 | 0.4 | 4000 | 0.5882 | 48.2661 |
|
||
|
|
| 0.5165 | 0.5 | 5000 | 0.5679 | 47.1259 |
|
||
|
|
| 0.5509 | 0.6 | 6000 | 0.5540 | 46.6359 |
|
||
|
|
| 0.639 | 0.7 | 7000 | 0.5466 | 46.5228 |
|
||
|
|
| 0.4715 | 0.8 | 8000 | 0.5400 | 45.9763 |
|
||
|
|
| 0.6306 | 0.9 | 9000 | 0.5363 | 45.1376 |
|
||
|
|
| 0.4598 | 1.0 | 10000 | 0.5352 | 45.4768 |
|
||
|
|
|
||
|
|
|
||
|
|
### Framework versions
|
||
|
|
|
||
|
|
- Transformers 4.36.2
|
||
|
|
- Pytorch 2.1.0+cu121
|
||
|
|
- Datasets 2.16.1
|
||
|
|
- Tokenizers 0.15.0
|