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# wav2vec2-common_voice-it_en

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - IT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0432
- Wer: 0.0322

## 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: 7
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 14
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.4885        | 0.7   | 1200  | 0.2958          | 0.2618 |
| 0.2986        | 1.4   | 2400  | 0.1802          | 0.1629 |
| 0.2515        | 2.1   | 3600  | 0.1379          | 0.1317 |
| 0.2013        | 2.8   | 4800  | 0.1208          | 0.1178 |
| 0.1651        | 3.5   | 6000  | 0.1110          | 0.1159 |
| 0.1559        | 4.2   | 7200  | 0.0923          | 0.0948 |
| 0.1337        | 4.9   | 8400  | 0.0928          | 0.0931 |
| 0.1162        | 5.6   | 9600  | 0.0753          | 0.0782 |
| 0.1164        | 6.3   | 10800 | 0.0700          | 0.0714 |
| 0.1057        | 7.0   | 12000 | 0.0630          | 0.0656 |
| 0.0904        | 7.7   | 13200 | 0.0619          | 0.0624 |
| 0.0807        | 8.4   | 14400 | 0.0609          | 0.0566 |
| 0.0759        | 9.1   | 15600 | 0.0514          | 0.0490 |
| 0.0657        | 9.8   | 16800 | 0.0504          | 0.0470 |
| 0.0556        | 10.5  | 18000 | 0.0511          | 0.0431 |
| 0.0534        | 11.2  | 19200 | 0.0484          | 0.0408 |
| 0.0498        | 11.9  | 20400 | 0.0436          | 0.0383 |
| 0.0441        | 12.6  | 21600 | 0.0458          | 0.0365 |
| 0.0398        | 13.3  | 22800 | 0.0471          | 0.0354 |
| 0.0379        | 14.0  | 24000 | 0.0402          | 0.0327 |
| 0.0333        | 14.7  | 25200 | 0.0438          | 0.0326 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"language": ["it"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "common_voice", "generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-common_voice-it_en", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition common_voice generated_from_trainer it license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #common_voice #generated_from_trainer #it #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-common\_voice-it\_en
=============================


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


* Loss: 0.0432
* Wer: 0.0322


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: 7
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 14
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 15.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 7
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 14
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 15.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #common_voice #generated_from_trainer #it #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 7
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 14
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 15.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3