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# wav2vec2_s-f-o_8batch_5sec_0.0001lr_unfrozen

This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4943
- Accuracy: 0.6667
- F1: 0.6742

## 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: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.003
- num_epochs: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.1376        | 1.0   | 131  | 2.1461          | 0.15     | 0.0802 |
| 1.3836        | 2.0   | 262  | 1.8662          | 0.4      | 0.3888 |
| 1.2382        | 2.99  | 393  | 1.6891          | 0.45     | 0.4245 |
| 0.8998        | 4.0   | 525  | 1.4406          | 0.6      | 0.5890 |
| 0.5064        | 5.0   | 656  | 1.2466          | 0.7      | 0.6632 |
| 0.5248        | 6.0   | 787  | 1.1712          | 0.7      | 0.6705 |
| 0.5376        | 6.99  | 918  | 1.3778          | 0.6667   | 0.6620 |
| 0.4291        | 8.0   | 1050 | 2.0535          | 0.6167   | 0.5799 |
| 0.4947        | 9.0   | 1181 | 1.3218          | 0.7333   | 0.7250 |
| 0.5743        | 10.0  | 1312 | 1.7264          | 0.6667   | 0.6534 |
| 0.3847        | 10.99 | 1443 | 1.9041          | 0.6333   | 0.6319 |
| 0.6198        | 12.0  | 1575 | 1.3526          | 0.7167   | 0.6856 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "wav2vec2_s-f-o_8batch_5sec_0.0001lr_unfrozen", "results": []}]}
transformers pytorch tensorboard wav2vec2 audio-classification generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2\_s-f-o\_8batch\_5sec\_0.0001lr\_unfrozen
=================================================


This model is a fine-tuned version of facebook/wav2vec2-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.4943
* Accuracy: 0.6667
* F1: 0.6742


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: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.003
* num\_epochs: 1000


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.003
* num\_epochs: 1000 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #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: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.003
* num\_epochs: 1000 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3