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# scream_tertius_dropout_replicate_test7a

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: 1.1799
- train_loss: 0.3145
- eval_wer: 11.6626
- eval_cer: 5.8907

## 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     | 1.3582    | 7.9231     | 169.1230 | 127.5435 |
| 1000  | 0.9203    | 0.9748     | 24.0256  | 9.2618   |
| 2000  | 0.9951    | 0.6747     | 18.7576  | 7.4326   |
| 3000  | 1.1073    | 0.5495     | 16.7479  | 7.1000   |
| 4000  | 1.1093    | 0.4612     | 14.4336  | 6.4147   |
| 5000  | 1.1719    | 0.4326     | 14.1900  | 6.2837   |
| 6000  | 1.2627    | 0.3998     | 12.8197  | 5.9814   |
| 7000  | 1.2785    | 0.3765     | 12.7893  | 6.1476   |
| 8000  | 1.1395    | 0.3869     | 12.5152  | 6.0519   |
| 9000  | 1.2327    | 0.3616     | 12.7893  | 6.1829   |
| 10000 | 1.0855    | 0.3620     | 11.4495  | 5.6790   |
| 11000 | 1.1018    | 0.3453     | 11.7540  | 5.7848   |
| 12000 | 0.9953    | 0.3486     | 11.7235  | 5.7294   |
| 13000 | 1.1321    | 0.3365     | 12.0280  | 6.0015   |
| 14000 | 1.2654    | 0.3335     | 11.6322  | 5.8050   |
| 15000 | 1.2149    | 0.3061     | 11.8453  | 5.8503   |
| 16000 | 1.1539    | 0.3090     | 11.9367  | 5.8503   |
| 17000 | 1.2530    | 0.3103     | 11.7540  | 5.8251   |
| 18000 | 1.1925    | 0.3209     | 11.4799  | 5.6790   |
| 19000 | 1.2155    | 0.2931     | 11.7235  | 5.9562   |
| 19999 | 1.1799    | 0.3145     | 11.6626  | 5.8907   |


### 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_tertius_dropout_replicate_test7a", "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\_test7a
===========================================


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: 1.1799
* train\_loss: 0.3145
* eval\_wer: 11.6626
* eval\_cer: 5.8907


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 4.29.0.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
* dropout: True
* dropout\_probability: 0.1 ### 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
* dropout: True
* dropout\_probability: 0.1 ### Training results ### Framework versions


* Transformers 4.29.0.dev0
* Datasets 2.12.0
* Tokenizers 0.13.3