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# wav2vec2-large-xls-r-300m-j-phoneme-colab-3

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_10_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6478
- Wer: 0.3336

## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| No log        | 1.0   | 397   | 1.0586          | 0.9425 |
| No log        | 2.0   | 794   | 0.5773          | 0.5847 |
| 1.9827        | 3.0   | 1191  | 0.5243          | 0.4882 |
| 1.9827        | 4.0   | 1588  | 0.4735          | 0.4624 |
| 1.9827        | 5.0   | 1985  | 0.4967          | 0.4789 |
| 0.6004        | 6.0   | 2382  | 0.4703          | 0.4246 |
| 0.6004        | 7.0   | 2779  | 0.4555          | 0.4194 |
| 0.4911        | 8.0   | 3176  | 0.4692          | 0.4284 |
| 0.4911        | 9.0   | 3573  | 0.4589          | 0.3997 |
| 0.4911        | 10.0  | 3970  | 0.4988          | 0.4286 |
| 0.4275        | 11.0  | 4367  | 0.4851          | 0.4153 |
| 0.4275        | 12.0  | 4764  | 0.5020          | 0.4039 |
| 0.3784        | 13.0  | 5161  | 0.5491          | 0.4169 |
| 0.3784        | 14.0  | 5558  | 0.5211          | 0.4080 |
| 0.3784        | 15.0  | 5955  | 0.5124          | 0.3950 |
| 0.3362        | 16.0  | 6352  | 0.5121          | 0.3909 |
| 0.3362        | 17.0  | 6749  | 0.5503          | 0.3728 |
| 0.3046        | 18.0  | 7146  | 0.5363          | 0.3915 |
| 0.3046        | 19.0  | 7543  | 0.6112          | 0.4076 |
| 0.3046        | 20.0  | 7940  | 0.5884          | 0.3755 |
| 0.2785        | 21.0  | 8337  | 0.5639          | 0.3793 |
| 0.2785        | 22.0  | 8734  | 0.6246          | 0.3742 |
| 0.2513        | 23.0  | 9131  | 0.6014          | 0.3714 |
| 0.2513        | 24.0  | 9528  | 0.6195          | 0.3697 |
| 0.2513        | 25.0  | 9925  | 0.6004          | 0.3729 |
| 0.2296        | 26.0  | 10322 | 0.5793          | 0.3585 |
| 0.2296        | 27.0  | 10719 | 0.6178          | 0.3628 |
| 0.2114        | 28.0  | 11116 | 0.5974          | 0.3507 |
| 0.2114        | 29.0  | 11513 | 0.6056          | 0.3432 |
| 0.2114        | 30.0  | 11910 | 0.6190          | 0.3536 |
| 0.1944        | 31.0  | 12307 | 0.6293          | 0.3550 |
| 0.1944        | 32.0  | 12704 | 0.6236          | 0.3535 |
| 0.1777        | 33.0  | 13101 | 0.6456          | 0.3503 |
| 0.1777        | 34.0  | 13498 | 0.6629          | 0.3444 |
| 0.1777        | 35.0  | 13895 | 0.6585          | 0.3432 |
| 0.1644        | 36.0  | 14292 | 0.6528          | 0.3455 |
| 0.1644        | 37.0  | 14689 | 0.6460          | 0.3437 |
| 0.1521        | 38.0  | 15086 | 0.6441          | 0.3360 |
| 0.1521        | 39.0  | 15483 | 0.6531          | 0.3350 |
| 0.1521        | 40.0  | 15880 | 0.6478          | 0.3336 |


### Framework versions

- Transformers 4.21.3
- Pytorch 1.10.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice_10_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-j-phoneme-colab-3", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_10_0 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_10_0 #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-large-xls-r-300m-j-phoneme-colab-3
===========================================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common\_voice\_10\_0 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.6478
* Wer: 0.3336


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: 2
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 40
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.21.3
* Pytorch 1.10.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 2
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 40
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.3
* Pytorch 1.10.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_10_0 #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 2
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 40
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.3
* Pytorch 1.10.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_10_0 #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 2
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 40
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.21.3
* Pytorch 1.10.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1