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# wav2vec2-xlsr-ft-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 - CY dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1127
- Wer: 0.0622

## 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: 64
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.1868        | 0.68  | 400   | 0.7819          | 0.6673 |
| 0.4668        | 1.35  | 800   | 0.2890          | 0.3116 |
| 0.266         | 2.03  | 1200  | 0.1848          | 0.1822 |
| 0.1767        | 2.7   | 1600  | 0.1603          | 0.1521 |
| 0.1459        | 3.38  | 2000  | 0.1458          | 0.1401 |
| 0.1254        | 4.06  | 2400  | 0.1358          | 0.1280 |
| 0.1061        | 4.73  | 2800  | 0.1281          | 0.1195 |
| 0.0925        | 5.41  | 3200  | 0.1321          | 0.1224 |
| 0.0859        | 6.09  | 3600  | 0.1333          | 0.1181 |
| 0.0765        | 6.76  | 4000  | 0.1284          | 0.1148 |
| 0.0713        | 7.44  | 4400  | 0.1177          | 0.1046 |
| 0.0664        | 8.11  | 4800  | 0.1231          | 0.1015 |
| 0.0639        | 8.79  | 5200  | 0.1249          | 0.1007 |
| 0.0595        | 9.47  | 5600  | 0.1162          | 0.0922 |
| 0.0551        | 10.14 | 6000  | 0.1182          | 0.0917 |
| 0.0529        | 10.82 | 6400  | 0.1188          | 0.0903 |
| 0.0485        | 11.5  | 6800  | 0.1130          | 0.0886 |
| 0.0467        | 12.17 | 7200  | 0.1206          | 0.0953 |
| 0.0442        | 12.85 | 7600  | 0.1253          | 0.0964 |
| 0.0411        | 13.52 | 8000  | 0.1111          | 0.0889 |
| 0.0409        | 14.2  | 8400  | 0.1167          | 0.0854 |
| 0.0396        | 14.88 | 8800  | 0.1120          | 0.0864 |
| 0.0373        | 15.55 | 9200  | 0.1150          | 0.0807 |
| 0.0371        | 16.23 | 9600  | 0.1190          | 0.0801 |
| 0.0354        | 16.91 | 10000 | 0.1145          | 0.0795 |
| 0.0318        | 17.58 | 10400 | 0.1161          | 0.0759 |
| 0.0292        | 18.26 | 10800 | 0.1203          | 0.0765 |
| 0.028         | 18.93 | 11200 | 0.1187          | 0.0756 |
| 0.0273        | 19.61 | 11600 | 0.1254          | 0.0802 |
| 0.0275        | 20.29 | 12000 | 0.1171          | 0.0733 |
| 0.0264        | 20.96 | 12400 | 0.1116          | 0.0726 |
| 0.025         | 21.64 | 12800 | 0.1175          | 0.0726 |
| 0.0238        | 22.32 | 13200 | 0.1109          | 0.0697 |
| 0.0224        | 22.99 | 13600 | 0.1149          | 0.0711 |
| 0.0216        | 23.67 | 14000 | 0.1144          | 0.0693 |
| 0.0211        | 24.34 | 14400 | 0.1133          | 0.0685 |
| 0.0197        | 25.02 | 14800 | 0.1179          | 0.0671 |
| 0.0183        | 25.7  | 15200 | 0.1178          | 0.0684 |
| 0.0181        | 26.37 | 15600 | 0.1135          | 0.0655 |
| 0.0174        | 27.05 | 16000 | 0.1149          | 0.0647 |
| 0.0163        | 27.73 | 16400 | 0.1125          | 0.0628 |
| 0.0159        | 28.4  | 16800 | 0.1150          | 0.0630 |
| 0.0155        | 29.08 | 17200 | 0.1143          | 0.0621 |
| 0.0149        | 29.75 | 17600 | 0.1129          | 0.0621 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3

{"language": ["cy"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "custom_common_voice.py", "generated_from_trainer"], "datasets": ["custom_common_voice"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-xlsr-ft-cy", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "CUSTOM_COMMON_VOICE.PY - CY", "type": "custom_common_voice", "config": "cy", "split": "test", "args": "Config: cy, Training split: train+validation, Eval split: test"}, "metrics": [{"type": "wer", "value": 0.06219015190275401, "name": "Wer"}]}]}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition custom_common_voice.py generated_from_trainer cy dataset:custom_common_voice license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #custom_common_voice.py #generated_from_trainer #cy #dataset-custom_common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us 

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


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


* Loss: 0.1127
* Wer: 0.0622


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: 64
* eval\_batch\_size: 128
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 128
* 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 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 64
* eval\_batch\_size: 128
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 128
* 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 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #custom_common_voice.py #generated_from_trainer #cy #dataset-custom_common_voice #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: 64
* eval\_batch\_size: 128
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 128
* 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 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.3