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# wav2vec2-xlsr-53-ft-ccv-btb-cy

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the CUSTOM_COMMON_VOICE.PY,TECHIAITH/BANC-TRAWSGRIFIADAU-BANGOR - CY dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1729
- Wer: 0.1562

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.3855        | 0.28  | 400  | 1.3323          | 0.8624 |
| 0.6301        | 0.56  | 800  | 0.4340          | 0.3828 |
| 0.4144        | 0.84  | 1200 | 0.3096          | 0.2935 |
| 0.3277        | 1.12  | 1600 | 0.2646          | 0.2432 |
| 0.2751        | 1.4   | 2000 | 0.2415          | 0.2251 |
| 0.2535        | 1.68  | 2400 | 0.2237          | 0.2094 |
| 0.2409        | 1.96  | 2800 | 0.2092          | 0.1968 |
| 0.1927        | 2.25  | 3200 | 0.1996          | 0.1840 |
| 0.1802        | 2.53  | 3600 | 0.1892          | 0.1762 |
| 0.171         | 2.81  | 4000 | 0.1815          | 0.1670 |
| 0.1521        | 3.09  | 4400 | 0.1789          | 0.1622 |
| 0.1327        | 3.37  | 4800 | 0.1742          | 0.1573 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"language": ["cy"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "custom_common_voice.py,techiaith/banc-trawsgrifiadau-bangor", "generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-xlsr-53-ft-ccv-btb-cy", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition custom_common_voice.py,techiaith/banc-trawsgrifiadau-bangor generated_from_trainer cy license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #custom_common_voice.py,techiaith/banc-trawsgrifiadau-bangor #generated_from_trainer #cy #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-xlsr-53-ft-ccv-btb-cy
==============================


This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the CUSTOM\_COMMON\_VOICE.PY,TECHIAITH/BANC-TRAWSGRIFIADAU-BANGOR - CY dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1729
* Wer: 0.1562


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: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 800
* training\_steps: 5000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 800
* training\_steps: 5000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #custom_common_voice.py,techiaith/banc-trawsgrifiadau-bangor #generated_from_trainer #cy #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 800
* training\_steps: 5000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3