---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: WAVLM_TITML_IDN_model
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8181137724550899
---

<!-- 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. -->

# WAVLM_TITML_IDN_model

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7585
- Accuracy: 0.8181

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 8.0217        | 0.98  | 31   | 7.7416          | 0.0472   |
| 5.1076        | 2.0   | 63   | 3.5170          | 0.0472   |
| 3.0131        | 2.98  | 94   | 2.9921          | 0.0876   |
| 3.0119        | 4.0   | 126  | 2.9580          | 0.0928   |
| 2.685         | 4.98  | 157  | 2.6591          | 0.0793   |
| 2.4513        | 6.0   | 189  | 2.3831          | 0.1257   |
| 2.4415        | 6.98  | 220  | 2.3518          | 0.1415   |
| 2.2998        | 8.0   | 252  | 2.2327          | 0.1864   |
| 2.1987        | 8.98  | 283  | 2.1297          | 0.1549   |
| 2.1206        | 10.0  | 315  | 2.0529          | 0.2118   |
| 2.0542        | 10.98 | 346  | 1.9592          | 0.2507   |
| 1.9693        | 12.0  | 378  | 1.8652          | 0.2792   |
| 1.8677        | 12.98 | 409  | 1.7811          | 0.3668   |
| 1.7369        | 14.0  | 441  | 1.7902          | 0.2493   |
| 1.6551        | 14.98 | 472  | 1.6558          | 0.3406   |
| 1.6176        | 16.0  | 504  | 1.5724          | 0.3585   |
| 1.5666        | 16.98 | 535  | 1.5822          | 0.4207   |
| 1.5103        | 18.0  | 567  | 1.5028          | 0.4379   |
| 1.4695        | 18.98 | 598  | 1.4276          | 0.4970   |
| 1.3016        | 20.0  | 630  | 1.3621          | 0.4798   |
| 1.2025        | 20.98 | 661  | 1.2016          | 0.5778   |
| 1.1211        | 22.0  | 693  | 1.2346          | 0.5644   |
| 1.0204        | 22.98 | 724  | 1.0743          | 0.6445   |
| 0.9365        | 24.0  | 756  | 1.0121          | 0.6759   |
| 0.8553        | 24.98 | 787  | 0.9246          | 0.7290   |
| 0.7698        | 26.0  | 819  | 0.8603          | 0.7612   |
| 0.7336        | 26.98 | 850  | 0.8072          | 0.7867   |
| 0.6965        | 28.0  | 882  | 0.7770          | 0.8009   |
| 0.6662        | 28.98 | 913  | 0.7640          | 0.8136   |
| 0.63          | 29.52 | 930  | 0.7585          | 0.8181   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1