---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: wav2vec2_capstone
  results: []
datasets:
- mozilla-foundation/common_voice_16_1
language:
- en
- ca
- rw
- be
- eo
- de
- fr
- ka
- es
- lg
- sw
- fa
- it
- mh
- zh
- ba
- ta
- ru
- eu
- th
- pt
- pl
- ja
pipeline_tag: audio-classification
---
<!-- 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_CAPSTONE_MODEL2

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on a subset of the common_voice_16_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3952
- Accuracy: 0.9098
- F1 score: 0.9097
## 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: 0.0003
- train_batch_size: 7
- eval_batch_size: 7
- seed: 42
- gradient_accumulation_steps: 11
- total_train_batch_size: 77
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 1.5222        | 1.0   | 513  | 1.4214          | 0.5477   | 0.5374   |
| 0.9554        | 2.0   | 1027 | 1.0182          | 0.6892   | 0.6826   |
| 0.6128        | 3.0   | 1541 | 0.6117          | 0.8205   | 0.8203   |
| 0.4882        | 4.0   | 2055 | 0.5092          | 0.8474   | 0.8478   |
| 0.2305        | 5.0   | 2569 | 0.5244          | 0.8643   | 0.8639   |
| 0.1219        | 6.0   | 3082 | 0.4169          | 0.8966   | 0.8966   |
| 0.0672        | 6.99  | 3591 | 0.3952          | 0.9098   | 0.9097   |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0