File size: 1,896 Bytes
b87ec76 951c2e1 b87ec76 951c2e1 b87ec76 a4175cb b87ec76 951c2e1 b87ec76 951c2e1 b87ec76 951c2e1 b87ec76 6b2a443 b87ec76 6b2a443 b87ec76 951c2e1 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-et-children
results: []
language:
- et
library_name: transformers
---
<!-- 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-large-v2-et-children
This model is a fine-tuned version of [agnesluhtaru/whisper-large-et-ERR2020-v2](https://huggingface.co/agnesluhtaru/whisper-large-et-ERR2020-v2) on an Estonian children's speech dataset.
More information about the model's performance and the data used for evaluation and training:
Luhtaru, Agnes; Jaaska, Rauno; Kruusamäe, Karl; Fishel, Mark (2023). Automatic Transcription for Estonian Children’s Speech. In: Proceedings of the 24th Nordic Conference on Computational Linguistics. [https://openreview.net/forum?id=xbPTfBIUby](https://openreview.net/forum?id=xbPTfBIUby)
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0302 | 4.03 | 500 | 0.2971 | 16.2892 |
| 0.0042 | 8.06 | 1000 | 0.3406 | 15.8551 |
| 0.0017 | 12.1 | 1500 | 0.3714 | 15.5585 |
| 0.0009 | 16.13 | 2000 | 0.3934 | 15.6445 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+rocm5.1.1
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2 |