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# Whisper Small Odia 10k steps

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the [Ranjit/or_in_dataset](https://huggingface.co/datasets/Ranjit/or_in_dataset) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2806
- Wer: 19.7720

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0384        | 0.49  | 1000  | 0.1349          | 40.3740 |
| 0.0175        | 0.98  | 2000  | 0.1601          | 22.6468 |
| 0.0091        | 1.46  | 3000  | 0.1817          | 23.1515 |
| 0.0082        | 1.95  | 4000  | 0.2125          | 23.9139 |
| 0.0048        | 2.44  | 5000  | 0.2110          | 20.2522 |
| 0.0037        | 2.93  | 6000  | 0.2270          | 21.4855 |
| 0.0017        | 3.42  | 7000  | 0.2534          | 20.2399 |
| 0.0018        | 3.9   | 8000  | 0.2706          | 20.7277 |
| 0.0005        | 4.39  | 9000  | 0.2806          | 19.7720 |
| 0.0006        | 4.88  | 10000 | 0.2929          | 20.9747 |


<!-- ### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.10.1
- Tokenizers 0.13.2 -->
{"language": ["or"], "license": "afl-3.0", "tags": ["whisper-event", "generated_from_trainer", "oriya"], "datasets": ["Ranjit/or_in_dataset"], "metrics": ["wer"], "pipeline_tag": "automatic-speech-recognition", "model-index": [{"name": "Whisper Small Odia 10k steps", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Ranjit/or_in_dataset", "type": "Ranjit/or_in_dataset", "split": "test"}, "metrics": [{"type": "wer", "value": 19.772043934466467, "name": "Wer"}]}]}]}
transformers pytorch tensorboard whisper automatic-speech-recognition whisper-event generated_from_trainer oriya or dataset:Ranjit/or_in_dataset license:afl-3.0 model-index endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #oriya #or #dataset-Ranjit/or_in_dataset #license-afl-3.0 #model-index #endpoints_compatible #has_space #region-us 

Whisper Small Odia 10k steps
============================


This model is a fine-tuned version of openai/whisper-small on the Ranjit/or\_in\_dataset dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2806
* Wer: 19.7720


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* training\_steps: 10000
* mixed\_precision\_training: Native AMP


### Training results




### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* training\_steps: 10000
* mixed\_precision\_training: Native AMP ### Training results
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #oriya #or #dataset-Ranjit/or_in_dataset #license-afl-3.0 #model-index #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* training\_steps: 10000
* mixed\_precision\_training: Native AMP ### Training results
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #oriya #or #dataset-Ranjit/or_in_dataset #license-afl-3.0 #model-index #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* training\_steps: 10000
* mixed\_precision\_training: Native AMP### Training results