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# scream_sextusdecimus_virtual_tsfix_small

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the NbAiLab/ncc_speech dataset.
It achieves the following results on the evaluation set:
- step: 19999
- eval_loss: 0.2913
- train_loss: 0.6610
- eval_wer: 8.7151
- eval_cer: 3.8962
- eval_exact_wer: 8.7151
- eval_exact_cer: 3.8962

## 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: 5e-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: 11920
- num_beams: 5
- dropout: True
- bpe_dropout_probability: 0.1
- activation_dropout_probability: 0.1

### Training results

| step  | eval_loss | train_loss | eval_wer | eval_cer | eval_exact_wer | eval_exact_cer |
|:-----:|:---------:|:----------:|:--------:|:--------:|:--------------:|:--------------:|
| 0     | 1.2807    | 3.0725     | 196.6092 | 157.4275 | 196.6092       | 157.4275       |
| 1000  | 0.5902    | 1.0592     | 15.1695  | 4.8382   | 15.1695        | 4.8382         |
| 2000  | 0.4240    | 0.8640     | 11.3623  | 3.9308   | 11.3623        | 3.9308         |
| 3000  | 0.4213    | 0.7930     | 9.4587   | 3.3537   | 9.4587         | 3.3537         |
| 4000  | 0.4353    | 0.7986     | 9.3694   | 3.5263   | 9.3694         | 3.5263         |
| 5000  | 0.4697    | 0.7580     | 9.7858   | 4.1478   | 9.7858         | 4.1478         |
| 6000  | 0.4535    | 0.7003     | 10.0238  | 4.2119   | 10.0238        | 4.2119         |
| 7000  | 0.4608    | 0.7296     | 8.8638   | 3.4228   | 8.8638         | 3.4228         |
| 8000  | 0.3902    | 0.7053     | 8.9233   | 3.6003   | 8.9233         | 3.6003         |
| 9000  | 0.3575    | 0.7124     | 9.3992   | 3.9702   | 9.3992         | 3.9702         |
| 10000 | 0.3648    | 0.6858     | 8.8043   | 3.4326   | 8.8043         | 3.4326         |
| 11000 | 0.3033    | 0.6916     | 9.1315   | 3.7236   | 9.1315         | 3.7236         |
| 12000 | 0.3021    | 0.7028     | 8.9827   | 3.6052   | 8.9827         | 3.6052         |
| 13000 | 0.2959    | 0.6567     | 8.6556   | 3.4918   | 8.6556         | 3.4918         |
| 14000 | 0.3055    | 0.6828     | 8.9827   | 3.6496   | 8.9827         | 3.6496         |
| 15000 | 0.2930    | 0.6707     | 8.8043   | 3.7976   | 8.8043         | 3.7976         |
| 16000 | 0.2822    | 0.6523     | 8.5068   | 3.5806   | 8.5068         | 3.5806         |
| 17000 | 0.2809    | 0.6581     | 8.6853   | 3.7828   | 8.6853         | 3.7828         |
| 18000 | 0.2927    | 0.6455     | 9.1315   | 4.2513   | 9.1315         | 4.2513         |
| 19000 | 0.2922    | 0.6369     | 9.1017   | 4.1034   | 9.1017         | 4.1034         |
| 19999 | 0.2913    | 0.6610     | 8.7151   | 3.8962   | 8.7151         | 3.8962         |


### Framework versions

- Transformers 4.30.0.dev0
- Datasets 2.12.1.dev0
- Tokenizers 0.13.3

{"language": ["no"], "license": "apache-2.0", "tags": ["audio", "asr", "automatic-speech-recognition", "hf-asr-leaderboard"], "model-index": [{"name": "scream_sextusdecimus_virtual_tsfix_small", "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\_sextusdecimus\_virtual\_tsfix\_small
============================================


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


* step: 19999
* eval\_loss: 0.2913
* train\_loss: 0.6610
* eval\_wer: 8.7151
* eval\_cer: 3.8962
* eval\_exact\_wer: 8.7151
* eval\_exact\_cer: 3.8962


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: 5e-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: 11920
* num\_beams: 5
* dropout: True
* bpe\_dropout\_probability: 0.1
* activation\_dropout\_probability: 0.1


### Training results



### Framework versions


* Transformers 4.30.0.dev0
* Datasets 2.12.1.dev0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 11920
* num\_beams: 5
* dropout: True
* bpe\_dropout\_probability: 0.1
* activation\_dropout\_probability: 0.1 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Datasets 2.12.1.dev0
* 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: 5e-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: 11920
* num\_beams: 5
* dropout: True
* bpe\_dropout\_probability: 0.1
* activation\_dropout\_probability: 0.1 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Datasets 2.12.1.dev0
* Tokenizers 0.13.3