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# 

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - PT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2290
- Wer: 0.2382

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 15.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.0952        | 0.64  | 500   | 3.0982          | 1.0    |
| 1.7975        | 1.29  | 1000  | 0.7887          | 0.5651 |
| 1.4138        | 1.93  | 1500  | 0.5238          | 0.4389 |
| 1.344         | 2.57  | 2000  | 0.4775          | 0.4318 |
| 1.2737        | 3.21  | 2500  | 0.4648          | 0.4075 |
| 1.2554        | 3.86  | 3000  | 0.4069          | 0.3678 |
| 1.1996        | 4.5   | 3500  | 0.3914          | 0.3668 |
| 1.1427        | 5.14  | 4000  | 0.3694          | 0.3572 |
| 1.1372        | 5.78  | 4500  | 0.3568          | 0.3501 |
| 1.0831        | 6.43  | 5000  | 0.3331          | 0.3253 |
| 1.1074        | 7.07  | 5500  | 0.3332          | 0.3352 |
| 1.0536        | 7.71  | 6000  | 0.3131          | 0.3152 |
| 1.0248        | 8.35  | 6500  | 0.3024          | 0.3023 |
| 1.0075        | 9.0   | 7000  | 0.2948          | 0.3028 |
| 0.979         | 9.64  | 7500  | 0.2796          | 0.2853 |
| 0.9594        | 10.28 | 8000  | 0.2719          | 0.2789 |
| 0.9172        | 10.93 | 8500  | 0.2620          | 0.2695 |
| 0.9047        | 11.57 | 9000  | 0.2537          | 0.2596 |
| 0.8777        | 12.21 | 9500  | 0.2438          | 0.2525 |
| 0.8629        | 12.85 | 10000 | 0.2409          | 0.2493 |
| 0.8575        | 13.5  | 10500 | 0.2366          | 0.2440 |
| 0.8361        | 14.14 | 11000 | 0.2317          | 0.2385 |
| 0.8126        | 14.78 | 11500 | 0.2290          | 0.2382 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0

{"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "robust-speech-event", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "xls-r-300m-pt", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "dataset": {"name": "Common Voice 8.0 pt", "type": "mozilla-foundation/common_voice_8_0", "args": "pt"}, "metrics": [{"type": "wer", "value": 19.361, "name": "Test WER"}, {"type": "cer", "value": 5.533, "name": "Test CER"}, {"type": "wer", "value": 19.36, "name": "Test WER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Dev Data", "type": "speech-recognition-community-v2/dev_data", "args": "fr"}, "metrics": [{"type": "wer", "value": 47.812, "name": "Validation WER"}, {"type": "cer", "value": 18.805, "name": "Validation CER"}, {"type": "wer", "value": 48.01, "name": "Test WER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Test Data", "type": "speech-recognition-community-v2/eval_data", "args": "pt"}, "metrics": [{"type": "wer", "value": 49.21, "name": "Test WER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition robust-speech-event mozilla-foundation/common_voice_8_0 generated_from_trainer hf-asr-leaderboard pt dataset:mozilla-foundation/common_voice_8_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #robust-speech-event #mozilla-foundation/common_voice_8_0 #generated_from_trainer #hf-asr-leaderboard #pt #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - PT dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2290
* Wer: 0.2382


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: 0.0002
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1500
* num\_epochs: 15.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1500
* num\_epochs: 15.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #robust-speech-event #mozilla-foundation/common_voice_8_0 #generated_from_trainer #hf-asr-leaderboard #pt #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1500
* num\_epochs: 15.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #robust-speech-event #mozilla-foundation/common_voice_8_0 #generated_from_trainer #hf-asr-leaderboard #pt #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1500
* num\_epochs: 15.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0