---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- bayartsogt/mongolian_speech_commands
model-index:
- name: wav2vec2-base-mn-pretrain-42h-mn-silence-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-mn-silence-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: 0.0562
- Mn Acc: 0.9830
- Mn F1: 0.9832
- Silence Acc: 1.0
- Silence F1: 1.0

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mn Acc | Mn F1  | Silence Acc | Silence F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-----------:|:----------:|
| No log        | 0.4   | 8    | 2.0276          | 0.0455 | 0.0239 | 1.0         | 1.0        |
| 2.3615        | 0.8   | 16   | 1.1112          | 0.0057 | 0.0108 | 1.0         | 1.0        |
| 2.0154        | 1.2   | 24   | 0.6836          | 0.6307 | 0.5627 | 0.9975      | 0.9988     |
| 1.5733        | 1.6   | 32   | 0.4493          | 0.7898 | 0.7652 | 0.9975      | 0.9988     |
| 1.1148        | 2.0   | 40   | 0.3264          | 0.8409 | 0.8202 | 1.0         | 1.0        |
| 1.1148        | 2.4   | 48   | 0.2490          | 0.8864 | 0.8768 | 1.0         | 1.0        |
| 0.7937        | 2.8   | 56   | 0.1739          | 0.9545 | 0.9540 | 1.0         | 1.0        |
| 0.586         | 3.2   | 64   | 0.1425          | 0.9659 | 0.9664 | 1.0         | 1.0        |
| 0.4445        | 3.6   | 72   | 0.1137          | 0.9659 | 0.9659 | 1.0         | 1.0        |
| 0.3892        | 4.0   | 80   | 0.0942          | 0.9773 | 0.9772 | 1.0         | 1.0        |
| 0.3892        | 4.4   | 88   | 0.0914          | 0.9716 | 0.9717 | 1.0         | 1.0        |
| 0.3341        | 4.8   | 96   | 0.0748          | 0.9773 | 0.9775 | 1.0         | 1.0        |
| 0.2863        | 5.2   | 104  | 0.0670          | 0.9886 | 0.9886 | 1.0         | 1.0        |
| 0.2622        | 5.6   | 112  | 0.0697          | 0.9830 | 0.9832 | 1.0         | 1.0        |
| 0.2222        | 6.0   | 120  | 0.0638          | 0.9830 | 0.9832 | 1.0         | 1.0        |
| 0.2222        | 6.4   | 128  | 0.0580          | 0.9886 | 0.9886 | 1.0         | 1.0        |
| 0.213         | 6.8   | 136  | 0.0575          | 0.9830 | 0.9832 | 1.0         | 1.0        |
| 0.2082        | 7.2   | 144  | 0.0587          | 0.9830 | 0.9832 | 1.0         | 1.0        |
| 0.202         | 7.6   | 152  | 0.0582          | 0.9830 | 0.9832 | 1.0         | 1.0        |
| 0.1936        | 8.0   | 160  | 0.0562          | 0.9830 | 0.9832 | 1.0         | 1.0        |


### Framework versions

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