---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-base_lr_3e-4
  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. -->

# wav2vec2-base_lr_3e-4

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: 0.0682
- Accuracy: 0.9784

## 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: 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: 15

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.7893        | 0.9851  | 33   | 1.5529          | 0.4602   |
| 0.9637        | 2.0     | 67   | 0.8562          | 0.7563   |
| 0.5758        | 2.9851  | 100  | 0.4980          | 0.8276   |
| 0.5401        | 4.0     | 134  | 0.3442          | 0.8875   |
| 0.3908        | 4.9851  | 167  | 0.4630          | 0.8322   |
| 0.348         | 6.0     | 201  | 0.2102          | 0.9260   |
| 0.309         | 6.9851  | 234  | 0.1996          | 0.9391   |
| 0.305         | 8.0     | 268  | 0.3001          | 0.9185   |
| 0.2311        | 8.9851  | 301  | 0.2150          | 0.9335   |
| 0.2362        | 10.0    | 335  | 0.1218          | 0.9550   |
| 0.1929        | 10.9851 | 368  | 0.1334          | 0.9550   |
| 0.1781        | 12.0    | 402  | 0.1077          | 0.9597   |
| 0.15          | 12.9851 | 435  | 0.0749          | 0.9719   |
| 0.1437        | 14.0    | 469  | 0.0710          | 0.9756   |
| 0.1135        | 14.7761 | 495  | 0.0682          | 0.9784   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1