---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test-model
  results: []
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/khackho01125-CMC-University/huggingface/runs/fddm7hnz)
# test-model

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2342
- Accuracy: 0.9356

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- training_steps: 600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0226        | 0.9639 | 60   | 0.8861          | 0.5453   |
| 0.8233        | 1.9277 | 120  | 0.6863          | 0.7123   |
| 0.672         | 2.8916 | 180  | 0.4994          | 0.7988   |
| 0.5346        | 3.8554 | 240  | 0.4163          | 0.8692   |
| 0.4306        | 4.8193 | 300  | 0.3459          | 0.8934   |
| 0.3544        | 5.7831 | 360  | 0.3317          | 0.8853   |
| 0.3214        | 6.7470 | 420  | 0.2763          | 0.9115   |
| 0.2778        | 7.7108 | 480  | 0.2877          | 0.9296   |
| 0.2264        | 8.6747 | 540  | 0.2487          | 0.9336   |
| 0.2127        | 9.6386 | 600  | 0.2342          | 0.9356   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1