---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: CS337_finetune_wav2vec_base
  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. -->

# CS337_finetune_wav2vec_base

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: 0.9758
- Accuracy: 0.5838

## 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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9835        | 0.97  | 28   | 0.9852          | 0.6256   |
| 1.0709        | 1.98  | 57   | 0.9559          | 0.6193   |
| 2.2881        | 2.99  | 86   | 1.3049          | 0.5203   |
| 1.5153        | 4.0   | 115  | 1.7062          | 0.3604   |
| 1.5127        | 4.97  | 143  | 1.3469          | 0.4683   |
| 1.4081        | 5.98  | 172  | 1.1282          | 0.5063   |
| 1.5358        | 6.99  | 201  | 1.1630          | 0.5355   |
| 1.4543        | 8.0   | 230  | 1.6172          | 0.3426   |
| 1.4626        | 8.97  | 258  | 1.1863          | 0.5241   |
| 1.3419        | 9.98  | 287  | 1.3211          | 0.4898   |
| 1.2167        | 10.99 | 316  | 1.1622          | 0.5381   |
| 1.3479        | 12.0  | 345  | 1.1126          | 0.5355   |
| 1.2712        | 12.97 | 373  | 1.1934          | 0.5102   |
| 1.3099        | 13.98 | 402  | 1.0652          | 0.5241   |
| 1.1829        | 14.99 | 431  | 1.0393          | 0.5241   |
| 1.3834        | 16.0  | 460  | 1.0916          | 0.5508   |
| 1.1997        | 16.97 | 488  | 1.0677          | 0.5799   |
| 1.1304        | 17.98 | 517  | 0.9980          | 0.5863   |
| 1.0456        | 18.99 | 546  | 0.9734          | 0.5863   |
| 1.0446        | 19.48 | 560  | 0.9758          | 0.5838   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1