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# scream_duo_dropout_bpe_dropout

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the NbAiLab/NCC_speech_all_v5 dataset.
It achieves the following results on the evaluation set:
- step: 19999
- eval_loss: 5.2383
- train_loss: 0.4761
- eval_wer: 10.1096
- eval_cer: 4.9735

## 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: 2e-05
- lr_scheduler_type: linear
- per_device_train_batch_size: 32
- total_train_batch_size_per_node: 128
- total_train_batch_size: 1024
- total_optimization_steps: 20,000
- starting_optimization_step: None
- finishing_optimization_step: 20,000
- num_train_dataset_workers: 32
- num_hosts: 8
- total_num_training_examples: 20,480,000
- steps_per_epoch: 1314
- num_beams: 5

### Training results

| step  | eval_loss | train_loss | eval_wer | eval_cer |
|:-----:|:---------:|:----------:|:--------:|:--------:|
| 0     | 4.2078    | 2.2707     | 169.1230 | 127.5435 |
| 1000  | 3.2725    | 0.8044     | 18.8490  | 7.9113   |
| 2000  | 2.8829    | 0.7114     | 12.7893  | 5.2205   |
| 3000  | 2.5190    | 0.6461     | 11.6931  | 5.1247   |
| 4000  | 2.5935    | 0.5883     | 10.8100  | 4.8325   |
| 5000  | 2.3213    | 0.5753     | 10.7186  | 4.8677   |
| 6000  | 3.2012    | 0.5495     | 10.6273  | 5.0491   |
| 7000  | 2.9775    | 0.5279     | 10.8100  | 5.0441   |
| 8000  | 3.1645    | 0.5412     | 9.9574   | 4.8929   |
| 9000  | 2.9499    | 0.5191     | 11.0840  | 7.1504   |
| 10000 | 3.7657    | 0.5215     | 10.5968  | 5.0189   |
| 11000 | 3.7694    | 0.5086     | 9.9574   | 4.8375   |
| 12000 | 3.9640    | 0.5121     | 10.3228  | 4.9685   |
| 13000 | 4.2364    | 0.4982     | 10.3532  | 5.0088   |
| 14000 | 4.5940    | 0.4908     | 9.9574   | 4.8627   |
| 15000 | 4.7101    | 0.4696     | 10.1401  | 5.0239   |
| 16000 | 4.7501    | 0.4680     | 9.8965   | 4.7317   |
| 17000 | 4.9145    | 0.4751     | 10.0792  | 5.0239   |
| 18000 | 5.1751    | 0.4783     | 10.0183  | 4.9332   |
| 19000 | 5.2207    | 0.4566     | 10.0183  | 4.9131   |
| 19999 | 5.2383    | 0.4761     | 10.1096  | 4.9735   |


### Framework versions

- Transformers 4.29.0.dev0
- Datasets 2.12.0
- Tokenizers 0.13.3

{"language": ["no"], "license": "apache-2.0", "tags": ["audio", "asr", "automatic-speech-recognition", "hf-asr-leaderboard"], "model-index": [{"name": "scream_duo_dropout_bpe_dropout", "results": []}]}
transformers jax tensorboard whisper automatic-speech-recognition audio asr hf-asr-leaderboard no license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #jax #tensorboard #whisper #automatic-speech-recognition #audio #asr #hf-asr-leaderboard #no #license-apache-2.0 #endpoints_compatible #region-us 

scream\_duo\_dropout\_bpe\_dropout
==================================


This model is a fine-tuned version of openai/whisper-small on the NbAiLab/NCC\_speech\_all\_v5 dataset.
It achieves the following results on the evaluation set:


* step: 19999
* eval\_loss: 5.2383
* train\_loss: 0.4761
* eval\_wer: 10.1096
* eval\_cer: 4.9735


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: 2e-05
* lr\_scheduler\_type: linear
* per\_device\_train\_batch\_size: 32
* total\_train\_batch\_size\_per\_node: 128
* total\_train\_batch\_size: 1024
* total\_optimization\_steps: 20,000
* starting\_optimization\_step: None
* finishing\_optimization\_step: 20,000
* num\_train\_dataset\_workers: 32
* num\_hosts: 8
* total\_num\_training\_examples: 20,480,000
* steps\_per\_epoch: 1314
* num\_beams: 5


### Training results



### Framework versions


* Transformers 4.29.0.dev0
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* lr\_scheduler\_type: linear
* per\_device\_train\_batch\_size: 32
* total\_train\_batch\_size\_per\_node: 128
* total\_train\_batch\_size: 1024
* total\_optimization\_steps: 20,000
* starting\_optimization\_step: None
* finishing\_optimization\_step: 20,000
* num\_train\_dataset\_workers: 32
* num\_hosts: 8
* total\_num\_training\_examples: 20,480,000
* steps\_per\_epoch: 1314
* num\_beams: 5 ### Training results ### Framework versions


* Transformers 4.29.0.dev0
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #jax #tensorboard #whisper #automatic-speech-recognition #audio #asr #hf-asr-leaderboard #no #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* lr\_scheduler\_type: linear
* per\_device\_train\_batch\_size: 32
* total\_train\_batch\_size\_per\_node: 128
* total\_train\_batch\_size: 1024
* total\_optimization\_steps: 20,000
* starting\_optimization\_step: None
* finishing\_optimization\_step: 20,000
* num\_train\_dataset\_workers: 32
* num\_hosts: 8
* total\_num\_training\_examples: 20,480,000
* steps\_per\_epoch: 1314
* num\_beams: 5 ### Training results ### Framework versions


* Transformers 4.29.0.dev0
* Datasets 2.12.0
* Tokenizers 0.13.3