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# libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-take-3

This model is a fine-tuned version of [rohitp1/libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-take-2](https://huggingface.co/rohitp1/libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-take-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 236.1198
- Wer: 0.2607

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 388.1305      | 0.45  | 200  | 228.0258        | 0.2599 |
| 376.7096      | 0.9   | 400  | 226.8922        | 0.2566 |
| 384.1615      | 1.35  | 600  | 228.5904        | 0.2571 |
| 373.8909      | 1.79  | 800  | 229.0286        | 0.2563 |
| 385.2149      | 2.24  | 1000 | 230.8802        | 0.2575 |
| 384.5473      | 2.69  | 1200 | 230.1264        | 0.2563 |
| 383.9426      | 3.14  | 1400 | 232.5964        | 0.2569 |
| 385.9253      | 3.59  | 1600 | 237.4036        | 0.2599 |
| 396.9868      | 4.04  | 1800 | 236.1198        | 0.2607 |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-take-3", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 

libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-take-3
======================================================================


This model is a fine-tuned version of rohitp1/libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-take-2 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 236.1198
* Wer: 0.2607


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: 0.0002
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.3
* num\_epochs: 30
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.23.1
* Pytorch 1.12.1
* Datasets 2.6.1
* Tokenizers 0.13.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.3
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.23.1
* Pytorch 1.12.1
* Datasets 2.6.1
* Tokenizers 0.13.1
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.3
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.23.1
* Pytorch 1.12.1
* Datasets 2.6.1
* Tokenizers 0.13.1
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.3
* num\_epochs: 30
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.23.1
* Pytorch 1.12.1
* Datasets 2.6.1
* Tokenizers 0.13.1