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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-Mongolian-cv17-base
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: mn
split: validation
args: mn
metrics:
- name: Wer
type: wer
value: 0.7902951968892054
---
<!-- 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-large-xlsr-Mongolian-cv17-base
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9632
- Wer: 0.7903
## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| No log | 1.1940 | 40 | 13.1486 | 1.0009 |
| No log | 2.3881 | 80 | 7.6639 | 1.0 |
| No log | 3.5821 | 120 | 3.4345 | 1.0 |
| No log | 4.7761 | 160 | 3.1527 | 1.0 |
| No log | 5.9701 | 200 | 3.1223 | 1.0 |
| No log | 7.1642 | 240 | 3.1137 | 1.0 |
| No log | 8.3582 | 280 | 3.1017 | 1.0 |
| No log | 9.5522 | 320 | 3.0909 | 1.0 |
| No log | 10.7463 | 360 | 3.0363 | 1.0 |
| 5.1112 | 11.9403 | 400 | 2.8364 | 1.0 |
| 5.1112 | 13.1343 | 440 | 2.0134 | 1.0078 |
| 5.1112 | 14.3284 | 480 | 1.3866 | 1.0511 |
| 5.1112 | 15.5224 | 520 | 1.1292 | 0.9320 |
| 5.1112 | 16.7164 | 560 | 1.0117 | 0.9017 |
| 5.1112 | 17.9104 | 600 | 0.9756 | 0.8339 |
| 5.1112 | 19.1045 | 640 | 0.9632 | 0.7903 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|