---
base_model: facebook/wav2vec2-large-xlsr-53
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: xlsr-nomi-nmcpc
  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. -->

# xlsr-nomi-nmcpc

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.2574

## 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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 132
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step  | Validation Loss | Wer    |
|:-------------:|:--------:|:-----:|:---------------:|:------:|
| 4.7569        | 3.8835   | 200   | 3.0327          | 1.0    |
| 2.9033        | 7.7670   | 400   | 2.5777          | 1.0    |
| 2.006         | 11.6505  | 600   | 0.7689          | 0.7298 |
| 0.7612        | 15.5340  | 800   | 0.2026          | 0.4191 |
| 0.3581        | 19.4175  | 1000  | 0.0966          | 0.3489 |
| 0.2432        | 23.3010  | 1200  | 0.0406          | 0.3128 |
| 0.1625        | 27.1845  | 1400  | 0.0479          | 0.3106 |
| 0.1391        | 31.0680  | 1600  | 0.0172          | 0.2915 |
| 0.1157        | 34.9515  | 1800  | 0.0110          | 0.2851 |
| 0.1016        | 38.8350  | 2000  | 0.0096          | 0.2766 |
| 0.0807        | 42.7184  | 2200  | 0.0162          | 0.2723 |
| 0.0673        | 46.6019  | 2400  | 0.0093          | 0.2681 |
| 0.0695        | 50.4854  | 2600  | 0.0305          | 0.2851 |
| 0.0589        | 54.3689  | 2800  | 0.0058          | 0.2638 |
| 0.0508        | 58.2524  | 3000  | 0.0172          | 0.2660 |
| 0.0503        | 62.1359  | 3200  | 0.0070          | 0.2660 |
| 0.0516        | 66.0194  | 3400  | 0.0017          | 0.2660 |
| 0.0435        | 69.9029  | 3600  | 0.0037          | 0.2617 |
| 0.0378        | 73.7864  | 3800  | 0.0020          | 0.2638 |
| 0.0325        | 77.6699  | 4000  | 0.0061          | 0.2702 |
| 0.031         | 81.5534  | 4200  | 0.0036          | 0.2617 |
| 0.0292        | 85.4369  | 4400  | 0.0075          | 0.2660 |
| 0.0281        | 89.3204  | 4600  | 0.0006          | 0.2532 |
| 0.0334        | 93.2039  | 4800  | 0.0007          | 0.2574 |
| 0.0307        | 97.0874  | 5000  | 0.0029          | 0.2596 |
| 0.0232        | 100.9709 | 5200  | 0.0025          | 0.2553 |
| 0.0228        | 104.8544 | 5400  | 0.0010          | 0.2596 |
| 0.0216        | 108.7379 | 5600  | 0.0014          | 0.2638 |
| 0.0207        | 112.6214 | 5800  | 0.0005          | 0.2596 |
| 0.0163        | 116.5049 | 6000  | 0.0021          | 0.2596 |
| 0.0232        | 120.3883 | 6200  | 0.0173          | 0.2638 |
| 0.0247        | 124.2718 | 6400  | 0.0102          | 0.2596 |
| 0.0198        | 128.1553 | 6600  | 0.0003          | 0.2553 |
| 0.0124        | 132.0388 | 6800  | 0.0001          | 0.2574 |
| 0.0117        | 135.9223 | 7000  | 0.0001          | 0.2574 |
| 0.0131        | 139.8058 | 7200  | 0.0002          | 0.2574 |
| 0.0119        | 143.6893 | 7400  | 0.0001          | 0.2574 |
| 0.0103        | 147.5728 | 7600  | 0.0001          | 0.2574 |
| 0.0083        | 151.4563 | 7800  | 0.0001          | 0.2574 |
| 0.0115        | 155.3398 | 8000  | 0.0001          | 0.2574 |
| 0.0112        | 159.2233 | 8200  | 0.0001          | 0.2574 |
| 0.0128        | 163.1068 | 8400  | 0.0001          | 0.2574 |
| 0.0062        | 166.9903 | 8600  | 0.0001          | 0.2574 |
| 0.0057        | 170.8738 | 8800  | 0.0000          | 0.2574 |
| 0.0072        | 174.7573 | 9000  | 0.0000          | 0.2574 |
| 0.0061        | 178.6408 | 9200  | 0.0000          | 0.2574 |
| 0.0047        | 182.5243 | 9400  | 0.0000          | 0.2574 |
| 0.0063        | 186.4078 | 9600  | 0.0000          | 0.2574 |
| 0.0043        | 190.2913 | 9800  | 0.0000          | 0.2574 |
| 0.006         | 194.1748 | 10000 | 0.0000          | 0.2574 |
| 0.0042        | 198.0583 | 10200 | 0.0000          | 0.2574 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1