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# hubert-large-ls960-ft

This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the galsenai/waxal_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3272
- Accuracy: 0.9413
- Precision: 0.9865
- F1: 0.9628

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|
| 4.7142        | 1.01  | 500   | 5.2765          | 0.0      | 0.0       | 0.0    |
| 4.396         | 2.02  | 1000  | 5.4145          | 0.0      | 0.0       | 0.0    |
| 3.8883        | 3.04  | 1500  | 4.4336          | 0.0474   | 0.0408    | 0.0104 |
| 2.7848        | 4.05  | 2000  | 3.9772          | 0.1300   | 0.1281    | 0.0964 |
| 1.8649        | 5.06  | 2500  | 3.4482          | 0.1576   | 0.3339    | 0.1547 |
| 1.3084        | 6.07  | 3000  | 2.9703          | 0.3081   | 0.5296    | 0.3402 |
| 0.9868        | 7.08  | 3500  | 2.3985          | 0.4687   | 0.8032    | 0.5353 |
| 0.7679        | 8.1   | 4000  | 1.7937          | 0.6521   | 0.8389    | 0.7095 |
| 0.6232        | 9.11  | 4500  | 1.4768          | 0.7389   | 0.8698    | 0.7847 |
| 0.5126        | 10.12 | 5000  | 1.0542          | 0.8287   | 0.9443    | 0.8763 |
| 0.4453        | 11.13 | 5500  | 0.9050          | 0.8518   | 0.9511    | 0.8960 |
| 0.3775        | 12.15 | 6000  | 0.6996          | 0.8928   | 0.9662    | 0.9266 |
| 0.3568        | 13.16 | 6500  | 0.6157          | 0.8958   | 0.9743    | 0.9285 |
| 0.3165        | 14.17 | 7000  | 0.4925          | 0.9151   | 0.9764    | 0.9436 |
| 0.2951        | 15.18 | 7500  | 0.4992          | 0.9038   | 0.9773    | 0.9369 |
| 0.2763        | 16.19 | 8000  | 0.5212          | 0.9072   | 0.9821    | 0.9404 |
| 0.2634        | 17.21 | 8500  | 0.5201          | 0.9087   | 0.9817    | 0.9418 |
| 0.2422        | 18.22 | 9000  | 0.4504          | 0.9235   | 0.9840    | 0.9514 |
| 0.236         | 19.23 | 9500  | 0.3829          | 0.9257   | 0.9825    | 0.9518 |
| 0.2272        | 20.24 | 10000 | 0.4632          | 0.9155   | 0.9822    | 0.9451 |
| 0.226         | 21.25 | 10500 | 0.4731          | 0.9159   | 0.9837    | 0.9470 |
| 0.2129        | 22.27 | 11000 | 0.3814          | 0.9299   | 0.9832    | 0.9549 |
| 0.2009        | 23.28 | 11500 | 0.4119          | 0.9257   | 0.9814    | 0.9515 |
| 0.1973        | 24.29 | 12000 | 0.4310          | 0.9216   | 0.9843    | 0.9493 |
| 0.1965        | 25.3  | 12500 | 0.3272          | 0.9413   | 0.9865    | 0.9628 |
| 0.1989        | 26.32 | 13000 | 0.4231          | 0.9242   | 0.9878    | 0.9528 |
| 0.1916        | 27.33 | 13500 | 0.3978          | 0.9284   | 0.9876    | 0.9559 |
| 0.1849        | 28.34 | 14000 | 0.4529          | 0.9216   | 0.9865    | 0.9507 |
| 0.1844        | 29.35 | 14500 | 0.3854          | 0.9314   | 0.9864    | 0.9566 |
| 0.1831        | 30.36 | 15000 | 0.4178          | 0.9257   | 0.9853    | 0.9528 |
| 0.1778        | 31.38 | 15500 | 0.3737          | 0.9360   | 0.9884    | 0.9606 |


### 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": "hubert-large-ls960-ft", "results": []}]}
transformers pytorch hubert audio-classification generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #hubert #audio-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

hubert-large-ls960-ft
=====================


This model is a fine-tuned version of facebook/hubert-large-ls960-ft on the galsenai/waxal\_dataset dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3272
* Accuracy: 0.9413
* Precision: 0.9865
* F1: 0.9628


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 #hubert #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 #hubert #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