# 

This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - SV-SE dataset.
It achieves the following results on the evaluation set ("test" split, without LM):
- Loss: 0.1318
- Wer: 0.1121

## 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: 7.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9099        | 10.42 | 1000 | 2.8369          | 1.0    |
| 1.0745        | 20.83 | 2000 | 0.1957          | 0.1673 |
| 0.934         | 31.25 | 3000 | 0.1579          | 0.1389 |
| 0.8691        | 41.66 | 4000 | 0.1457          | 0.1290 |
| 0.8328        | 52.08 | 5000 | 0.1435          | 0.1205 |
| 0.8068        | 62.5  | 6000 | 0.1350          | 0.1191 |
| 0.7822        | 72.91 | 7000 | 0.1347          | 0.1155 |
| 0.7769        | 83.33 | 8000 | 0.1321          | 0.1131 |
| 0.7678        | 93.75 | 9000 | 0.1321          | 0.1115 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 2.2.2
- Tokenizers 0.11.0

{"language": ["sv"], "license": "cc0-1.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_9_0", "generated_from_trainer", "sv"], "datasets": ["mozilla-foundation/common_voice_9_0"], "model-index": [{"name": "XLS-R-300M - Swedish", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "mozilla-foundation/common_voice_9_0", "type": "mozilla-foundation/common_voice_9_0", "split": "test", "args": "sv-SE"}, "metrics": [{"type": "wer", "value": 7.72, "name": "Test WER"}, {"type": "cer", "value": 2.61, "name": "Test CER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "speech-recognition-community-v2/dev_data", "type": "speech-recognition-community-v2/dev_data", "split": "validation", "args": "sv"}, "metrics": [{"type": "wer", "value": 16.23, "name": "Test WER"}, {"type": "cer", "value": 8.21, "name": "Test CER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "speech-recognition-community-v2/dev_data", "type": "speech-recognition-community-v2/dev_data", "split": "test", "args": "sv"}, "metrics": [{"type": "wer", "value": 15.08, "name": "Test WER"}, {"type": "cer", "value": 7.51, "name": "Test CER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_9_0 generated_from_trainer sv dataset:mozilla-foundation/common_voice_9_0 license:cc0-1.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_9_0 #generated_from_trainer #sv #dataset-mozilla-foundation/common_voice_9_0 #license-cc0-1.0 #model-index #endpoints_compatible #region-us 


This model is a fine-tuned version of KBLab/wav2vec2-large-voxrex on the MOZILLA-FOUNDATION/COMMON\_VOICE\_9\_0 - SV-SE dataset.
It achieves the following results on the evaluation set ("test" split, without LM):


* Loss: 0.1318
* Wer: 0.1121


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: 7.5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 2.2.2
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 2.2.2
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_9_0 #generated_from_trainer #sv #dataset-mozilla-foundation/common_voice_9_0 #license-cc0-1.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 2.2.2
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_9_0 #generated_from_trainer #sv #dataset-mozilla-foundation/common_voice_9_0 #license-cc0-1.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.2
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 2.2.2
* Tokenizers 0.11.0