
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# whisper-tiny-cb

This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2940
- Wer: 0.1396
- Mer: 0.1346
- Wil: 0.2111
- Wip: 0.7889

## 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: 3e-06
- train_batch_size: 48
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Mer    | Wil    | Wip    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|
| No log        | 0.1   | 10   | 3.5619          | 0.4169 | 0.3723 | 0.5496 | 0.4504 |
| No log        | 0.21  | 20   | 3.5594          | 0.4169 | 0.3723 | 0.5496 | 0.4504 |
| No log        | 0.31  | 30   | 3.5458          | 0.4159 | 0.3714 | 0.5483 | 0.4517 |
| No log        | 0.41  | 40   | 3.5232          | 0.4130 | 0.3694 | 0.5466 | 0.4534 |
| 3.2935        | 0.52  | 50   | 3.4551          | 0.4120 | 0.3705 | 0.5481 | 0.4519 |
| 3.2935        | 0.62  | 60   | 3.3467          | 0.4110 | 0.3693 | 0.5459 | 0.4541 |
| 3.2935        | 0.72  | 70   | 3.2663          | 0.4130 | 0.3710 | 0.5485 | 0.4515 |
| 3.2935        | 0.82  | 80   | 3.1465          | 0.4100 | 0.3687 | 0.5455 | 0.4545 |
| 3.2935        | 0.93  | 90   | 3.0399          | 0.4031 | 0.3638 | 0.5396 | 0.4604 |
| 2.9491        | 1.03  | 100  | 2.9119          | 0.4002 | 0.3608 | 0.5345 | 0.4655 |
| 2.9491        | 1.13  | 110  | 2.8013          | 0.3982 | 0.3594 | 0.5332 | 0.4668 |
| 2.9491        | 1.24  | 120  | 2.6663          | 0.4051 | 0.3643 | 0.5379 | 0.4621 |
| 2.9491        | 1.34  | 130  | 2.5040          | 0.4022 | 0.3623 | 0.5341 | 0.4659 |
| 2.9491        | 1.44  | 140  | 2.3220          | 0.3972 | 0.3604 | 0.5254 | 0.4746 |
| 2.3522        | 1.55  | 150  | 2.1172          | 0.3638 | 0.3342 | 0.4918 | 0.5082 |
| 2.3522        | 1.65  | 160  | 1.8729          | 0.3609 | 0.3315 | 0.4867 | 0.5133 |
| 2.3522        | 1.75  | 170  | 1.6150          | 0.3707 | 0.3409 | 0.4917 | 0.5083 |
| 2.3522        | 1.86  | 180  | 1.3932          | 0.4464 | 0.4131 | 0.5460 | 0.4540 |
| 2.3522        | 1.96  | 190  | 1.2081          | 0.3658 | 0.3454 | 0.4773 | 0.5227 |
| 1.4367        | 2.06  | 200  | 0.9976          | 0.3333 | 0.3127 | 0.4403 | 0.5597 |
| 1.4367        | 2.16  | 210  | 0.8126          | 0.2852 | 0.2698 | 0.4117 | 0.5883 |
| 1.4367        | 2.27  | 220  | 0.6996          | 0.2753 | 0.2610 | 0.3962 | 0.6038 |
| 1.4367        | 2.37  | 230  | 0.6348          | 0.2380 | 0.2264 | 0.3540 | 0.6460 |
| 1.4367        | 2.47  | 240  | 0.5850          | 0.2262 | 0.2156 | 0.3414 | 0.6586 |
| 0.7217        | 2.58  | 250  | 0.5463          | 0.2153 | 0.2049 | 0.3260 | 0.6740 |
| 0.7217        | 2.68  | 260  | 0.5130          | 0.2055 | 0.1957 | 0.3103 | 0.6897 |
| 0.7217        | 2.78  | 270  | 0.4870          | 0.1898 | 0.1819 | 0.2911 | 0.7089 |
| 0.7217        | 2.89  | 280  | 0.4659          | 0.1809 | 0.1739 | 0.2792 | 0.7208 |
| 0.7217        | 2.99  | 290  | 0.4492          | 0.1819 | 0.1747 | 0.2778 | 0.7222 |
| 0.5116        | 3.09  | 300  | 0.4375          | 0.1770 | 0.1698 | 0.2706 | 0.7294 |
| 0.5116        | 3.2   | 310  | 0.4252          | 0.1799 | 0.1722 | 0.2720 | 0.7280 |
| 0.5116        | 3.3   | 320  | 0.4112          | 0.1780 | 0.1704 | 0.2704 | 0.7296 |
| 0.5116        | 3.4   | 330  | 0.3990          | 0.1721 | 0.1653 | 0.2626 | 0.7374 |
| 0.5116        | 3.51  | 340  | 0.3887          | 0.1583 | 0.1523 | 0.2417 | 0.7583 |
| 0.4371        | 3.61  | 350  | 0.3777          | 0.1593 | 0.1534 | 0.2429 | 0.7571 |
| 0.4371        | 3.71  | 360  | 0.3625          | 0.1563 | 0.1503 | 0.2366 | 0.7634 |
| 0.4371        | 3.81  | 370  | 0.3523          | 0.1504 | 0.1449 | 0.2283 | 0.7717 |
| 0.4371        | 3.92  | 380  | 0.3488          | 0.1485 | 0.1430 | 0.2256 | 0.7744 |
| 0.4371        | 4.02  | 390  | 0.3443          | 0.1475 | 0.1420 | 0.2239 | 0.7761 |
| 0.3618        | 4.12  | 400  | 0.3383          | 0.1465 | 0.1411 | 0.2230 | 0.7770 |
| 0.3618        | 4.23  | 410  | 0.3323          | 0.1455 | 0.1404 | 0.2209 | 0.7791 |
| 0.3618        | 4.33  | 420  | 0.3284          | 0.1514 | 0.1461 | 0.2297 | 0.7703 |
| 0.3618        | 4.43  | 430  | 0.3201          | 0.1475 | 0.1419 | 0.2215 | 0.7785 |
| 0.3618        | 4.54  | 440  | 0.3140          | 0.1436 | 0.1383 | 0.2163 | 0.7837 |
| 0.3404        | 4.64  | 450  | 0.3087          | 0.1436 | 0.1384 | 0.2158 | 0.7842 |
| 0.3404        | 4.74  | 460  | 0.3040          | 0.1386 | 0.1342 | 0.2095 | 0.7905 |
| 0.3404        | 4.85  | 470  | 0.3006          | 0.1347 | 0.1305 | 0.2050 | 0.7950 |
| 0.3404        | 4.95  | 480  | 0.2963          | 0.1347 | 0.1304 | 0.2040 | 0.7960 |
| 0.3404        | 5.05  | 490  | 0.2944          | 0.1426 | 0.1372 | 0.2136 | 0.7864 |
| 0.3062        | 5.15  | 500  | 0.2955          | 0.1396 | 0.1345 | 0.2094 | 0.7906 |
| 0.3062        | 5.26  | 510  | 0.2940          | 0.1396 | 0.1346 | 0.2111 | 0.7889 |


### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["audiofolder"], "metrics": ["wer"], "model-index": [{"name": "whisper-tiny-cb", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "audiofolder", "type": "audiofolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "wer", "value": 0.13962635201573254, "name": "Wer"}]}]}]}
transformers pytorch tensorboard whisper automatic-speech-recognition generated_from_trainer dataset:audiofolder license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #dataset-audiofolder #license-apache-2.0 #model-index #endpoints_compatible #region-us 

whisper-tiny-cb
===============


This model is a fine-tuned version of openai/URL on the audiofolder dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2940
* Wer: 0.1396
* Mer: 0.1346
* Wil: 0.2111
* Wip: 0.7889


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: 3e-06
* train\_batch\_size: 48
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 1500
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-06
* train\_batch\_size: 48
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 1500
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #dataset-audiofolder #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-06
* train\_batch\_size: 48
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 1500
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #dataset-audiofolder #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-06
* train\_batch\_size: 48
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 1500
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3