File size: 2,344 Bytes
976dee6 bc5193e 976dee6 bc5193e 976dee6 bc5193e 976dee6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 |
---
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
|