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# lbri500

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3739
- Wer: 0.2225

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.02  | 200  | 3.4253          | 1.0000 |
| No log        | 0.04  | 400  | 1.4537          | 0.6604 |
| 2.74          | 0.06  | 600  | 1.1070          | 0.5025 |
| 2.74          | 0.09  | 800  | 0.8496          | 0.4207 |
| 0.3705        | 0.11  | 1000 | 0.8767          | 0.4470 |
| 0.3705        | 0.13  | 1200 | 0.7220          | 0.3894 |
| 0.3705        | 0.15  | 1400 | 0.7478          | 0.4116 |
| 0.3273        | 0.17  | 1600 | 0.6434          | 0.3624 |
| 0.3273        | 0.19  | 1800 | 2.7013          | 0.5531 |
| 0.2925        | 0.22  | 2000 | 1.1436          | 0.3535 |
| 0.2925        | 0.24  | 2200 | 1.1855          | 0.3640 |
| 0.2925        | 0.26  | 2400 | 0.7101          | 0.3149 |
| 0.2651        | 0.28  | 2600 | 0.5961          | 0.3177 |
| 0.2651        | 0.3   | 2800 | 0.8519          | 0.3193 |
| 0.2491        | 0.32  | 3000 | 0.5905          | 0.2986 |
| 0.2491        | 0.34  | 3200 | 0.5106          | 0.2890 |
| 0.2491        | 0.37  | 3400 | 0.5417          | 0.2984 |
| 0.2403        | 0.39  | 3600 | 0.6281          | 0.3248 |
| 0.2403        | 0.41  | 3800 | 0.5387          | 0.2924 |
| 0.2245        | 0.43  | 4000 | 0.7894          | 0.3626 |
| 0.2245        | 0.45  | 4200 | 0.5342          | 0.2928 |
| 0.2245        | 0.47  | 4400 | 0.3809          | 0.2605 |
| 0.2111        | 0.49  | 4600 | 0.3956          | 0.2551 |
| 0.2111        | 0.52  | 4800 | 0.6096          | 0.2653 |
| 0.1974        | 0.54  | 5000 | 0.4152          | 0.2546 |
| 0.1974        | 0.56  | 5200 | 0.4424          | 0.2573 |
| 0.1974        | 0.58  | 5400 | 0.5658          | 0.2741 |
| 0.193         | 0.6   | 5600 | 0.4838          | 0.2555 |
| 0.193         | 0.62  | 5800 | 0.4207          | 0.2506 |
| 0.1807        | 0.65  | 6000 | 0.4004          | 0.2472 |
| 0.1807        | 0.67  | 6200 | 0.3907          | 0.2524 |
| 0.1807        | 0.69  | 6400 | 0.4393          | 0.2738 |
| 0.1708        | 0.71  | 6600 | 0.5922          | 0.2680 |
| 0.1708        | 0.73  | 6800 | 0.5787          | 0.2751 |
| 0.1644        | 0.75  | 7000 | 0.4308          | 0.2452 |
| 0.1644        | 0.77  | 7200 | 0.3662          | 0.2294 |
| 0.1644        | 0.8   | 7400 | 0.6298          | 0.2600 |
| 0.1532        | 0.82  | 7600 | 0.4775          | 0.2383 |
| 0.1532        | 0.84  | 7800 | 0.3913          | 0.2196 |
| 0.148         | 0.86  | 8000 | 0.3752          | 0.2098 |
| 0.148         | 0.88  | 8200 | 0.3315          | 0.2115 |
| 0.148         | 0.9   | 8400 | 0.3518          | 0.2157 |
| 0.1401        | 0.93  | 8600 | 0.3517          | 0.2159 |
| 0.1401        | 0.95  | 8800 | 0.3515          | 0.2180 |
| 0.1351        | 0.97  | 9000 | 0.3792          | 0.2203 |
| 0.1351        | 0.99  | 9200 | 0.3739          | 0.2225 |


### Framework versions

- Transformers 4.27.2
- Pytorch 1.10.0
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "lbri500", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

lbri500
=======


This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3739
* Wer: 0.2225


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: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 1
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.2
* Pytorch 1.10.0
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 1
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.2
* Pytorch 1.10.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 1
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.2
* Pytorch 1.10.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 1
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.27.2
* Pytorch 1.10.0
* Datasets 2.10.1
* Tokenizers 0.13.2