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# wav2vec2-xlsr-fi-train-aug-lm-1B

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1499
- Wer: 0.1955

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 100
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6473        | 0.29  | 400  | 0.2857          | 0.3825 |
| 0.6039        | 0.58  | 800  | 0.2459          | 0.3476 |
| 0.4757        | 0.87  | 1200 | 0.2338          | 0.3274 |
| 0.4473        | 1.15  | 1600 | 0.2246          | 0.3128 |
| 0.4322        | 1.44  | 2000 | 0.1962          | 0.2805 |
| 0.3961        | 1.73  | 2400 | 0.2070          | 0.2797 |
| 0.3642        | 2.02  | 2800 | 0.1790          | 0.2473 |
| 0.3561        | 2.31  | 3200 | 0.1769          | 0.2375 |
| 0.282         | 2.6   | 3600 | 0.1672          | 0.2263 |
| 0.2978        | 2.89  | 4000 | 0.1636          | 0.2192 |
| 0.2722        | 3.17  | 4400 | 0.1637          | 0.2102 |
| 0.2924        | 3.46  | 4800 | 0.1506          | 0.2021 |
| 0.2631        | 3.75  | 5200 | 0.1499          | 0.1955 |


### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0

{"language": "fi", "tags": ["generated_from_trainer", "mozilla-foundation/common_voice_7_0", "audio", "automatic-speech-recognition", "speech"], "datasets": ["mozilla-foundation/common_voice_7_0"], "metrics": ["wer", "cer"]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer mozilla-foundation/common_voice_7_0 audio speech fi dataset:mozilla-foundation/common_voice_7_0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #mozilla-foundation/common_voice_7_0 #audio #speech #fi #dataset-mozilla-foundation/common_voice_7_0 #endpoints_compatible #region-us 

wav2vec2-xlsr-fi-train-aug-lm-1B
================================


This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1499
* Wer: 0.1955


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: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* 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: 100
* num\_epochs: 4
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* 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: 100
* num\_epochs: 4
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #mozilla-foundation/common_voice_7_0 #audio #speech #fi #dataset-mozilla-foundation/common_voice_7_0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* 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: 100
* num\_epochs: 4
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #mozilla-foundation/common_voice_7_0 #audio #speech #fi #dataset-mozilla-foundation/common_voice_7_0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* 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: 100
* num\_epochs: 4
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0