---
base_model: microsoft/wavlm-base
tags:
- audio-classification
- generated_from_trainer
metrics:
- f1
model-index:
- name: wavlm-base_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. -->

# wavlm-base_4

This model is a fine-tuned version of [microsoft/wavlm-base](https://huggingface.co/microsoft/wavlm-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3325
- F1: 0.9459

## 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: 16
- eval_batch_size: 2
- seed: 0
- 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: 0.1
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3784        | 0.25  | 100  | 0.0784          | 0.9906 |
| 0.1125        | 0.5   | 200  | 0.0638          | 0.9925 |
| 0.1158        | 0.76  | 300  | 0.1716          | 0.9773 |
| 0.327         | 1.01  | 400  | 0.3308          | 0.9459 |
| 0.3346        | 1.26  | 500  | 0.3449          | 0.9459 |
| 0.3345        | 1.51  | 600  | 0.3316          | 0.9459 |
| 0.3313        | 1.76  | 700  | 0.3320          | 0.9459 |
| 0.3249        | 2.02  | 800  | 0.3327          | 0.9459 |
| 0.3403        | 2.27  | 900  | 0.3315          | 0.9459 |
| 0.3345        | 2.52  | 1000 | 0.3382          | 0.9459 |
| 0.3174        | 2.77  | 1100 | 0.3376          | 0.9459 |
| 0.3274        | 3.02  | 1200 | 0.3354          | 0.9459 |
| 0.3296        | 3.28  | 1300 | 0.3307          | 0.9459 |
| 0.3175        | 3.53  | 1400 | 0.3341          | 0.9459 |
| 0.3416        | 3.78  | 1500 | 0.3344          | 0.9459 |
| 0.3412        | 4.03  | 1600 | 0.3308          | 0.9459 |
| 0.3293        | 4.28  | 1700 | 0.3314          | 0.9459 |
| 0.3346        | 4.54  | 1800 | 0.3308          | 0.9459 |
| 0.3279        | 4.79  | 1900 | 0.3317          | 0.9459 |
| 0.3246        | 5.04  | 2000 | 0.3318          | 0.9459 |
| 0.3373        | 5.29  | 2100 | 0.3311          | 0.9459 |
| 0.3262        | 5.55  | 2200 | 0.3335          | 0.9459 |
| 0.3279        | 5.8   | 2300 | 0.3326          | 0.9459 |
| 0.3298        | 6.05  | 2400 | 0.3323          | 0.9459 |
| 0.3397        | 6.3   | 2500 | 0.3311          | 0.9459 |
| 0.3312        | 6.55  | 2600 | 0.3386          | 0.9459 |
| 0.3291        | 6.81  | 2700 | 0.3317          | 0.9459 |
| 0.3146        | 7.06  | 2800 | 0.3323          | 0.9459 |
| 0.3296        | 7.31  | 2900 | 0.3313          | 0.9459 |
| 0.3367        | 7.56  | 3000 | 0.3317          | 0.9459 |
| 0.3232        | 7.81  | 3100 | 0.3318          | 0.9459 |
| 0.3314        | 8.07  | 3200 | 0.3325          | 0.9459 |
| 0.3201        | 8.32  | 3300 | 0.3323          | 0.9459 |
| 0.3301        | 8.57  | 3400 | 0.3347          | 0.9459 |
| 0.3268        | 8.82  | 3500 | 0.3325          | 0.9459 |
| 0.3361        | 9.07  | 3600 | 0.3321          | 0.9459 |
| 0.3395        | 9.33  | 3700 | 0.3313          | 0.9459 |
| 0.3231        | 9.58  | 3800 | 0.3319          | 0.9459 |
| 0.3197        | 9.83  | 3900 | 0.3326          | 0.9459 |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.0.post302
- Datasets 2.14.5
- Tokenizers 0.13.3