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# pratyush_whisper_small_distil_libri360_enc_8_dec_6_batch_2_epoch_50

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9043
- Wer: 13.0427

## 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: 0.0005
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 512
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 6.8528        | 0.49  | 100  | 5.4707          | 94.5857 |
| 5.4115        | 0.98  | 200  | 4.7525          | 89.6667 |
| 4.44          | 1.48  | 300  | 2.5672          | 47.3154 |
| 2.71          | 1.97  | 400  | 2.0272          | 26.9788 |
| 2.2003        | 2.46  | 500  | 1.8737          | 20.2713 |
| 2.0566        | 2.95  | 600  | 1.8204          | 17.6620 |
| 1.9829        | 3.45  | 700  | 1.7948          | 16.2944 |
| 1.9501        | 3.94  | 800  | 1.7809          | 15.3891 |
| 1.9173        | 4.43  | 900  | 1.7755          | 15.0537 |
| 1.9025        | 4.93  | 1000 | 1.7754          | 14.7302 |
| 1.8847        | 5.42  | 1100 | 1.7820          | 14.6116 |
| 1.8776        | 5.91  | 1200 | 1.7795          | 14.1585 |
| 1.8661        | 6.4   | 1300 | 1.7807          | 13.9664 |
| 1.8647        | 6.9   | 1400 | 1.7841          | 13.9940 |
| 1.858         | 7.39  | 1500 | 1.7921          | 13.9489 |
| 1.8608        | 7.88  | 1600 | 1.7997          | 13.9269 |
| 1.858         | 8.37  | 1700 | 1.8084          | 13.9370 |
| 1.8621        | 8.87  | 1800 | 1.8160          | 13.8414 |
| 1.8633        | 9.36  | 1900 | 1.8221          | 13.9627 |
| 1.8663        | 9.85  | 2000 | 1.8259          | 14.0013 |
| 1.8667        | 10.34 | 2100 | 1.8429          | 13.9379 |
| 1.865         | 10.84 | 2200 | 1.8406          | 13.9011 |
| 1.8614        | 11.33 | 2300 | 1.8401          | 13.5887 |
| 1.8564        | 11.82 | 2400 | 1.8587          | 13.5739 |
| 1.8552        | 12.32 | 2500 | 1.8514          | 13.5620 |
| 1.8523        | 12.81 | 2600 | 1.8561          | 13.3295 |
| 1.8551        | 13.3  | 2700 | 1.8581          | 13.3148 |
| 1.8521        | 13.79 | 2800 | 1.8650          | 13.1594 |
| 1.8522        | 14.29 | 2900 | 1.8729          | 13.2385 |
| 1.8513        | 14.78 | 3000 | 1.8754          | 13.1778 |
| 1.8524        | 15.27 | 3100 | 1.8814          | 13.0611 |
| 1.8495        | 15.76 | 3200 | 1.8867          | 13.2504 |
| 1.8553        | 16.26 | 3300 | 1.8860          | 13.0942 |
| 1.8531        | 16.75 | 3400 | 1.8884          | 12.8175 |
| 1.8545        | 17.24 | 3500 | 1.9003          | 12.8598 |
| 1.8533        | 17.73 | 3600 | 1.8982          | 13.0381 |
| 1.8548        | 18.23 | 3700 | 1.9005          | 13.0299 |
| 1.8542        | 18.72 | 3800 | 1.9067          | 13.0289 |
| 1.8552        | 19.21 | 3900 | 1.9043          | 13.0427 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.7.0
- Tokenizers 0.11.0

{"tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "pratyush_whisper_small_distil_libri360_enc_8_dec_6_batch_2_epoch_50", "results": []}]}
transformers pytorch whisper automatic-speech-recognition generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #whisper #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 

pratyush\_whisper\_small\_distil\_libri360\_enc\_8\_dec\_6\_batch\_2\_epoch\_50
===============================================================================


This model is a fine-tuned version of [](URL on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.9043
* Wer: 13.0427


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: 0.0005
* train\_batch\_size: 2
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 512
* total\_train\_batch\_size: 1024
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 50
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1
* Datasets 2.7.0
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 2
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 512
* total\_train\_batch\_size: 1024
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 50
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1
* Datasets 2.7.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #whisper #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 2
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 512
* total\_train\_batch\_size: 1024
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 50
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1
* Datasets 2.7.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #whisper #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 2
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 512
* total\_train\_batch\_size: 1024
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 50
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1
* Datasets 2.7.0
* Tokenizers 0.11.0