---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xlsr-no-mi-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-no-mi-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: 0.0001
- Wer: 0.2617

## 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.8152        | 3.8835  | 200  | 3.0388          | 1.0    |
| 2.9502        | 7.7670  | 400  | 2.6587          | 1.0    |
| 2.233         | 11.6505 | 600  | 0.8485          | 0.7638 |
| 0.8492        | 15.5340 | 800  | 0.1759          | 0.4319 |
| 0.3659        | 19.4175 | 1000 | 0.0757          | 0.3489 |
| 0.2237        | 23.3010 | 1200 | 0.0338          | 0.3064 |
| 0.1608        | 27.1845 | 1400 | 0.0238          | 0.3    |
| 0.1265        | 31.0680 | 1600 | 0.0142          | 0.2766 |
| 0.0989        | 34.9515 | 1800 | 0.0145          | 0.2766 |
| 0.0803        | 38.8350 | 2000 | 0.0043          | 0.2681 |
| 0.0701        | 42.7184 | 2200 | 0.0032          | 0.2638 |
| 0.061         | 46.6019 | 2400 | 0.0022          | 0.2638 |
| 0.0507        | 50.4854 | 2600 | 0.0033          | 0.2702 |
| 0.0422        | 54.3689 | 2800 | 0.0054          | 0.2660 |
| 0.0382        | 58.2524 | 3000 | 0.0011          | 0.2553 |
| 0.0381        | 62.1359 | 3200 | 0.0032          | 0.2660 |
| 0.0332        | 66.0194 | 3400 | 0.0006          | 0.2574 |
| 0.025         | 69.9029 | 3600 | 0.0007          | 0.2596 |
| 0.0185        | 73.7864 | 3800 | 0.0002          | 0.2596 |
| 0.0169        | 77.6699 | 4000 | 0.0003          | 0.2617 |
| 0.0136        | 81.5534 | 4200 | 0.0003          | 0.2617 |
| 0.0166        | 85.4369 | 4400 | 0.0002          | 0.2617 |
| 0.0124        | 89.3204 | 4600 | 0.0001          | 0.2617 |
| 0.0114        | 93.2039 | 4800 | 0.0001          | 0.2617 |
| 0.0115        | 97.0874 | 5000 | 0.0001          | 0.2617 |


### Framework versions

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