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---
datasets:
- coscan-speech2
license: apache-2.0
metrics:
- accuracy
model-index:
- name: wav2vec2-base-coscan-no-area
results:
- dataset:
name: Coscan Speech
type: NbAiLab/coscan-speech
metrics:
- name: Test Accuracy
type: accuracy
value: 0.8360824410790649
- name: Validation Accuracy
type: accuracy
value: 0.9485961489524133
task:
name: Audio Classification
type: audio-classification
tags:
- generated_from_trainer
---
<!-- 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 |