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# 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
{"language": ["et"], "license": "apache-2.0", "library_name": "transformers", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "whisper-large-et-children", "results": []}]}
transformers pytorch tensorboard whisper automatic-speech-recognition generated_from_trainer et license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #et #license-apache-2.0 #endpoints_compatible #region-us 

whisper-large-v2-et-children
============================


This model is a fine-tuned version of 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. URL


### 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



### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.12.1+rocm5.1.1
* Datasets 2.7.1.dev0
* Tokenizers 0.13.2



### 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 ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.12.1+rocm5.1.1
* Datasets 2.7.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #et #license-apache-2.0 #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.12.1+rocm5.1.1
* Datasets 2.7.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #et #license-apache-2.0 #endpoints_compatible #region-us 
### 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### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.12.1+rocm5.1.1
* Datasets 2.7.1.dev0
* Tokenizers 0.13.2