File size: 1,230 Bytes
883f658
72707d3
 
 
 
 
 
 
 
 
125f42f
5a0441e
 
 
 
883f658
 
72707d3
 
883f658
72707d3
883f658
72707d3
883f658
72707d3
883f658
72707d3
883f658
72707d3
883f658
72707d3
883f658
72707d3
883f658
72707d3
883f658
72707d3
883f658
72707d3
883f658
72707d3
 
 
 
 
 
 
 
 
 
883f658
72707d3
883f658
72707d3
 
 
125f42f
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_16_0
model-index:
- name: w2v-bert-version-final
  results: []
pipeline_tag: automatic-speech-recognition
language:
- mn
metrics:
- wer
---

<!-- 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. -->

# w2v-bert-version-final

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_16_0 dataset.

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 8
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.0
- Datasets 2.19.0
- Tokenizers 0.19.1