---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- bayartsogt/mongolian_speech_commands
metrics:
- accuracy
- f1
model-index:
- name: wav2vec2-base-mn-pretrain-42h-finetuned-speech-commands
  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-mn-pretrain-42h-finetuned-speech-commands

This model is a fine-tuned version of [bayartsogt/wav2vec2-base-mn-pretrain-42h](https://huggingface.co/bayartsogt/wav2vec2-base-mn-pretrain-42h) on the Mongolian Speech Commands dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1007
- Accuracy: 0.9762
- F1: 0.9758

## 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: 128
- eval_batch_size: 128
- seed: 42
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.2273        | 1.0   | 17   | 2.2714          | 0.1190   | 0.0253 |
| 1.7478        | 2.0   | 34   | 1.2036          | 0.8452   | 0.8242 |
| 0.775         | 3.0   | 51   | 0.4755          | 0.9524   | 0.9526 |
| 0.4738        | 4.0   | 68   | 0.2056          | 0.9881   | 0.9878 |
| 0.3146        | 5.0   | 85   | 0.1485          | 0.9762   | 0.9765 |
| 0.2677        | 6.0   | 102  | 0.1277          | 0.9762   | 0.9758 |
| 0.2636        | 7.0   | 119  | 0.0919          | 0.9881   | 0.9880 |
| 0.2122        | 8.0   | 136  | 0.0903          | 0.9762   | 0.9758 |
| 0.1817        | 9.0   | 153  | 0.0782          | 0.9881   | 0.9880 |
| 0.198         | 10.0  | 170  | 0.0982          | 0.9762   | 0.9758 |
| 0.1436        | 11.0  | 187  | 0.1053          | 0.9762   | 0.9758 |
| 0.1111        | 12.0  | 204  | 0.1004          | 0.9762   | 0.9758 |
| 0.1607        | 13.0  | 221  | 0.1176          | 0.9762   | 0.9758 |
| 0.1209        | 14.0  | 238  | 0.1097          | 0.9762   | 0.9758 |
| 0.0974        | 15.0  | 255  | 0.1136          | 0.9762   | 0.9758 |
| 0.1351        | 16.0  | 272  | 0.0986          | 0.9762   | 0.9758 |
| 0.1008        | 17.0  | 289  | 0.1010          | 0.9762   | 0.9758 |
| 0.097         | 18.0  | 306  | 0.0781          | 0.9762   | 0.9758 |
| 0.0806        | 19.0  | 323  | 0.1106          | 0.9762   | 0.9758 |
| 0.0744        | 20.0  | 340  | 0.1007          | 0.9762   | 0.9758 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3