
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-base-coscan-no-area

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the coscan-speech2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3398
- Accuracy: 0.9486

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0015        | 1.0   | 6468 | 0.3398          | 0.9486   |


### Framework versions

- Transformers 4.22.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 2.4.1.dev0
- Tokenizers 0.12.1
{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["coscan-speech2"], "metrics": ["accuracy"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "wav2vec2-base-coscan-no-area", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "dataset": {"name": "Coscan Speech", "type": "NbAiLab/coscan-speech"}, "metrics": [{"type": "accuracy", "value": 0.8360824410790649, "name": "Test Accuracy"}, {"type": "accuracy", "value": 0.9485961489524133, "name": "Validation Accuracy"}]}]}]}
transformers pytorch tensorboard safetensors wav2vec2 audio-classification generated_from_trainer dataset:coscan-speech2 base_model:facebook/wav2vec2-base license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #wav2vec2 #audio-classification #generated_from_trainer #dataset-coscan-speech2 #base_model-facebook/wav2vec2-base #license-apache-2.0 #model-index #endpoints_compatible #region-us 

wav2vec2-base-coscan-no-area
============================


This model is a fine-tuned version of facebook/wav2vec2-base on the coscan-speech2 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3398
* Accuracy: 0.9486


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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 1


### Training results



### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 2.4.1.dev0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 2.4.1.dev0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #safetensors #wav2vec2 #audio-classification #generated_from_trainer #dataset-coscan-speech2 #base_model-facebook/wav2vec2-base #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 2.4.1.dev0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #safetensors #wav2vec2 #audio-classification #generated_from_trainer #dataset-coscan-speech2 #base_model-facebook/wav2vec2-base #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 1### Training results### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 2.4.1.dev0
* Tokenizers 0.12.1