---
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: 1.0701
- Accuracy: 0.6599

## 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: 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
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.97  | 28   | 1.2971          | 0.5876   |
| No log        | 1.98  | 57   | 1.1261          | 0.6320   |
| No log        | 2.99  | 86   | 1.0746          | 0.6104   |
| 1.156         | 4.0   | 115  | 1.0080          | 0.6396   |
| 1.156         | 4.97  | 143  | 0.9706          | 0.6650   |
| 1.156         | 5.98  | 172  | 0.9316          | 0.6815   |
| 1.156         | 6.99  | 201  | 0.9493          | 0.6662   |
| 0.834         | 8.0   | 230  | 0.9774          | 0.6612   |
| 0.834         | 8.97  | 258  | 0.9498          | 0.6548   |
| 0.834         | 9.98  | 287  | 1.0197          | 0.6472   |
| 0.834         | 10.99 | 316  | 0.9520          | 0.6637   |
| 0.641         | 12.0  | 345  | 0.9616          | 0.6650   |
| 0.641         | 12.97 | 373  | 1.0307          | 0.6523   |
| 0.641         | 13.98 | 402  | 1.0298          | 0.6675   |
| 0.641         | 14.99 | 431  | 1.0342          | 0.6574   |
| 0.4929        | 16.0  | 460  | 1.0520          | 0.6536   |
| 0.4929        | 16.97 | 488  | 1.0752          | 0.6472   |
| 0.4929        | 17.98 | 517  | 1.0643          | 0.6561   |
| 0.4929        | 18.99 | 546  | 1.0709          | 0.6612   |
| 0.4929        | 19.48 | 560  | 1.0701          | 0.6599   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0