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# scream_non_large_timestamp_test

This model is a fine-tuned version of [NbAiLab/scream_non_large_1e06_beams5_constantlr_long](https://huggingface.co/NbAiLab/scream_non_large_1e06_beams5_constantlr_long) on the NbAiLab/NCC_whisper_both_timestamp dataset.

## 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: 1e-06
- lr_scheduler_type: linear
- per_device_train_batch_size: 16
- total_train_batch_size_per_node: 64
- total_train_batch_size: 64
- total_optimization_steps: 5,000
- starting_optimization_step: None
- finishing_optimization_step: 5,000
- num_train_dataset_workers: 32
- num_hosts: 1
- total_num_training_examples: 320,000
- steps_per_epoch: 475
- num_beams: 5

### Training results

| step | eval_loss | train_loss | eval_wer | eval_cer |
|:----:|:---------:|:----------:|:--------:|:--------:|
| 0    | 0.5499    | 0.6409     | 10.5055  | 5.6538   |
| 500  | 0.4301    | 0.1060     | 10.1401  | 4.9232   |
| 1000 | 0.4168    | 0.0776     | 10.3837  | 4.8123   |
| 1500 | 0.4132    | 0.0689     | 10.5968  | 4.8123   |
| 2000 | 0.4176    | 0.0511     | 10.5968  | 4.6712   |
| 2500 | 0.4261    | 0.0454     | 11.0536  | 4.7871   |
| 3000 | 0.4385    | 0.0441     | 11.1449  | 4.7770   |


### 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_non_large_timestamp_test", "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\_non\_large\_timestamp\_test
===================================


This model is a fine-tuned version of NbAiLab/scream\_non\_large\_1e06\_beams5\_constantlr\_long on the NbAiLab/NCC\_whisper\_both\_timestamp dataset.


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: 1e-06
* lr\_scheduler\_type: linear
* per\_device\_train\_batch\_size: 16
* total\_train\_batch\_size\_per\_node: 64
* total\_train\_batch\_size: 64
* total\_optimization\_steps: 5,000
* starting\_optimization\_step: None
* finishing\_optimization\_step: 5,000
* num\_train\_dataset\_workers: 32
* num\_hosts: 1
* total\_num\_training\_examples: 320,000
* steps\_per\_epoch: 475
* 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: 1e-06
* lr\_scheduler\_type: linear
* per\_device\_train\_batch\_size: 16
* total\_train\_batch\_size\_per\_node: 64
* total\_train\_batch\_size: 64
* total\_optimization\_steps: 5,000
* starting\_optimization\_step: None
* finishing\_optimization\_step: 5,000
* num\_train\_dataset\_workers: 32
* num\_hosts: 1
* total\_num\_training\_examples: 320,000
* steps\_per\_epoch: 475
* 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: 1e-06
* lr\_scheduler\_type: linear
* per\_device\_train\_batch\_size: 16
* total\_train\_batch\_size\_per\_node: 64
* total\_train\_batch\_size: 64
* total\_optimization\_steps: 5,000
* starting\_optimization\_step: None
* finishing\_optimization\_step: 5,000
* num\_train\_dataset\_workers: 32
* num\_hosts: 1
* total\_num\_training\_examples: 320,000
* steps\_per\_epoch: 475
* num\_beams: 5 ### Training results ### Framework versions


* Transformers 4.29.0.dev0
* Datasets 2.12.0
* Tokenizers 0.13.3