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# wav2vec2-large-asr-th-2

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2310
- Wer: 0.3196
- Cer: 0.0878

## 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: 1e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 36
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.065         | 0.18  | 1000 | 0.5433          | 0.3259 | 0.0891 |
| 0.0792        | 0.36  | 2000 | 0.5453          | 0.3269 | 0.0901 |
| 0.1663        | 0.53  | 3000 | 0.4702          | 0.3299 | 0.0908 |
| 0.7971        | 0.71  | 4000 | 0.2513          | 0.3244 | 0.0889 |
| 0.7588        | 0.89  | 5000 | 0.2310          | 0.3196 | 0.0878 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
{"language": ["th"], "library_name": "transformers", "tags": ["generated_from_trainer"], "datasets": ["common_voice", "mozilla-foundation/common_voice_10_0"], "metrics": ["wer", "cer"], "pipeline_tag": "automatic-speech-recognition", "model-index": [{"name": "wav2vec2-large-asr-th-2", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer th dataset:common_voice dataset:mozilla-foundation/common_voice_10_0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #th #dataset-common_voice #dataset-mozilla-foundation/common_voice_10_0 #endpoints_compatible #region-us 

wav2vec2-large-asr-th-2
=======================


This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2310
* Wer: 0.3196
* Cer: 0.0878


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: 1e-05
* train\_batch\_size: 12
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 3
* total\_train\_batch\_size: 36
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 5000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 12
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 3
* total\_train\_batch\_size: 36
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 5000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #th #dataset-common_voice #dataset-mozilla-foundation/common_voice_10_0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 12
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 3
* total\_train\_batch\_size: 36
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 5000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #th #dataset-common_voice #dataset-mozilla-foundation/common_voice_10_0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 12
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 3
* total\_train\_batch\_size: 36
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 5000
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3