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# wav2vec2-large

This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the galsenai/waxal_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3413
- Accuracy: 0.9443
- Precision: 0.9780
- F1: 0.9604

## 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: 3e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 32.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|
| 4.6314        | 1.01  | 500   | 4.9165          | 0.0205   | 0.0028    | 0.0049 |
| 3.7739        | 2.02  | 1000  | 4.4491          | 0.0356   | 0.0750    | 0.0252 |
| 2.5035        | 3.04  | 1500  | 4.1429          | 0.1129   | 0.2672    | 0.1114 |
| 1.5633        | 4.05  | 2000  | 3.1973          | 0.3676   | 0.6598    | 0.3830 |
| 1.0538        | 5.06  | 2500  | 2.5479          | 0.5889   | 0.8417    | 0.6557 |
| 0.7422        | 6.07  | 3000  | 1.4494          | 0.7825   | 0.8921    | 0.8194 |
| 0.5762        | 7.08  | 3500  | 1.3168          | 0.7726   | 0.9277    | 0.8267 |
| 0.46          | 8.1   | 4000  | 0.8783          | 0.8564   | 0.9532    | 0.8982 |
| 0.4007        | 9.11  | 4500  | 0.7524          | 0.8738   | 0.9637    | 0.9137 |
| 0.3374        | 10.12 | 5000  | 0.6386          | 0.8852   | 0.9678    | 0.9221 |
| 0.3108        | 11.13 | 5500  | 0.5049          | 0.9106   | 0.9681    | 0.9373 |
| 0.2735        | 12.15 | 6000  | 0.6097          | 0.8905   | 0.9624    | 0.9226 |
| 0.2716        | 13.16 | 6500  | 0.4543          | 0.9000   | 0.9569    | 0.9206 |
| 0.2484        | 14.17 | 7000  | 0.3965          | 0.9272   | 0.9742    | 0.9489 |
| 0.228         | 15.18 | 7500  | 0.6807          | 0.8856   | 0.9777    | 0.9257 |
| 0.2307        | 16.19 | 8000  | 0.5219          | 0.9174   | 0.9802    | 0.9464 |
| 0.2169        | 17.21 | 8500  | 0.4630          | 0.9121   | 0.9677    | 0.9338 |
| 0.1997        | 18.22 | 9000  | 0.5152          | 0.9128   | 0.9740    | 0.9398 |
| 0.1921        | 19.23 | 9500  | 0.5105          | 0.9144   | 0.9867    | 0.9476 |
| 0.1825        | 20.24 | 10000 | 0.6302          | 0.9053   | 0.9832    | 0.9407 |
| 0.1786        | 21.25 | 10500 | 0.4602          | 0.9272   | 0.9813    | 0.9524 |
| 0.1671        | 22.27 | 11000 | 0.5443          | 0.9147   | 0.9794    | 0.9444 |
| 0.1623        | 23.28 | 11500 | 0.3413          | 0.9443   | 0.9780    | 0.9604 |
| 0.1595        | 24.29 | 12000 | 0.4478          | 0.9288   | 0.9813    | 0.9531 |
| 0.151         | 25.3  | 12500 | 0.4178          | 0.9360   | 0.9818    | 0.9571 |
| 0.1472        | 26.32 | 13000 | 0.4154          | 0.9356   | 0.9833    | 0.9578 |
| 0.1473        | 27.33 | 13500 | 0.4549          | 0.9318   | 0.9837    | 0.9561 |
| 0.131         | 28.34 | 14000 | 0.3574          | 0.9424   | 0.9845    | 0.9621 |
| 0.134         | 29.35 | 14500 | 0.4475          | 0.9333   | 0.9840    | 0.9568 |
| 0.1282        | 30.36 | 15000 | 0.4012          | 0.9382   | 0.9837    | 0.9591 |
| 0.1307        | 31.38 | 15500 | 0.3552          | 0.9428   | 0.9847    | 0.9624 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["audio-classification", "generated_from_trainer"], "metrics": ["accuracy", "precision", "f1"], "model-index": [{"name": "wav2vec2-large", "results": []}]}
transformers pytorch wav2vec2 audio-classification generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #audio-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-large
==============


This model is a fine-tuned version of facebook/wav2vec2-large on the galsenai/waxal\_dataset dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3413
* Accuracy: 0.9443
* Precision: 0.9780
* F1: 0.9604


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: 3e-05
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 0
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 48
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 32.0


### Training results



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 0
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 48
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 32.0 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #wav2vec2 #audio-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 0
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 48
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 32.0 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #wav2vec2 #audio-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 0
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 48
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 32.0### Training results### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.9.1.dev0
* Tokenizers 0.13.2