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# wav2vec2-xlsr-ft-cv13-cy

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - CY dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4552
- Wer: 0.2529

## 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
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.2113        | 1.95  | 400  | 0.8211          | 0.7142 |
| 0.5062        | 3.9   | 800  | 0.4197          | 0.4302 |
| 0.2767        | 5.85  | 1200 | 0.3882          | 0.3764 |
| 0.1793        | 7.8   | 1600 | 0.3928          | 0.3453 |
| 0.132         | 9.76  | 2000 | 0.4073          | 0.3331 |
| 0.1071        | 11.71 | 2400 | 0.4364          | 0.3138 |
| 0.0933        | 13.66 | 2800 | 0.4310          | 0.2973 |
| 0.0816        | 15.61 | 3200 | 0.4229          | 0.2926 |
| 0.0735        | 17.56 | 3600 | 0.4422          | 0.2889 |
| 0.0665        | 19.51 | 4000 | 0.4509          | 0.2821 |
| 0.0583        | 21.46 | 4400 | 0.4678          | 0.2734 |
| 0.0529        | 23.41 | 4800 | 0.4459          | 0.2655 |
| 0.048         | 25.37 | 5200 | 0.4466          | 0.2620 |
| 0.0428        | 27.32 | 5600 | 0.4565          | 0.2579 |
| 0.0422        | 29.27 | 6000 | 0.4550          | 0.2532 |


### 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", "mozilla-foundation/common_voice_13_0", "generated_from_trainer"], "datasets": ["common_voice_13_0"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-xlsr-ft-cv13-cy", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - CY", "type": "common_voice_13_0", "config": "cy", "split": "test", "args": "Config: cy, Training split: train+validation, Eval split: test"}, "metrics": [{"type": "wer", "value": 0.25285529013094593, "name": "Wer"}]}]}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_13_0 generated_from_trainer cy dataset:common_voice_13_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_13_0 #generated_from_trainer #cy #dataset-common_voice_13_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

wav2vec2-xlsr-ft-cv13-cy
========================


This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the MOZILLA-FOUNDATION/COMMON\_VOICE\_13\_0 - CY dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4552
* Wer: 0.2529


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
* num\_epochs: 30.0
* 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
* num\_epochs: 30.0
* 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 #mozilla-foundation/common_voice_13_0 #generated_from_trainer #cy #dataset-common_voice_13_0 #license-apache-2.0 #model-index #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
* num\_epochs: 30.0
* 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