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# scream_tertius_dropout_replicate_test7b

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: 0.6607
- train_loss: 0.3094
- eval_wer: 10.8709
- eval_cer: 5.1449

## 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
- dropout: True
- dropout_probability: 0.1

### Training results

| step  | eval_loss | train_loss | eval_wer | eval_cer |
|:-----:|:---------:|:----------:|:--------:|:--------:|
| 0     | 1.3578    | 8.1186     | 156.3946 | 118.6999 |
| 1000  | 0.7538    | 0.9632     | 23.5688  | 9.1509   |
| 2000  | 0.7164    | 0.6653     | 18.2704  | 7.4628   |
| 3000  | 0.7374    | 0.5403     | 15.1340  | 6.4853   |
| 4000  | 0.7819    | 0.4543     | 13.5810  | 6.0368   |
| 5000  | 0.8360    | 0.4266     | 12.2716  | 5.4775   |
| 6000  | 0.9197    | 0.3941     | 11.6017  | 5.2104   |
| 7000  | 0.9399    | 0.3705     | 11.8149  | 5.3515   |
| 8000  | 0.7468    | 0.3806     | 11.6017  | 5.2104   |
| 9000  | 0.7944    | 0.3562     | 11.5713  | 5.3212   |
| 10000 | 0.6599    | 0.3563     | 11.1145  | 5.1046   |
| 11000 | 0.6534    | 0.3394     | 11.2972  | 5.3313   |
| 12000 | 0.5689    | 0.3427     | 11.0536  | 5.2708   |
| 13000 | 0.5633    | 0.3313     | 11.1754  | 5.2557   |
| 14000 | 0.7331    | 0.3278     | 11.4495  | 5.4623   |
| 15000 | 0.6593    | 0.3011     | 11.1754  | 5.1902   |
| 16000 | 0.6180    | 0.3044     | 11.1449  | 5.2356   |
| 17000 | 0.6761    | 0.3058     | 10.9318  | 5.2053   |
| 18000 | 0.6697    | 0.3154     | 10.8709  | 5.1499   |
| 19000 | 0.6730    | 0.2888     | 11.0231  | 5.2658   |
| 19999 | 0.6607    | 0.3094     | 10.8709  | 5.1449   |


### Framework versions

- Transformers 4.30.0.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_tertius_dropout_replicate_test7b", "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\_tertius\_dropout\_replicate\_test7b
===========================================


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: 0.6607
* train\_loss: 0.3094
* eval\_wer: 10.8709
* eval\_cer: 5.1449


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
* dropout: True
* dropout\_probability: 0.1


### Training results



### Framework versions


* Transformers 4.30.0.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
* dropout: True
* dropout\_probability: 0.1 ### Training results ### Framework versions


* Transformers 4.30.0.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
* dropout: True
* dropout\_probability: 0.1 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Datasets 2.12.0
* Tokenizers 0.13.3