---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xlsr-nomimo-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-nomimo-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: 0.0002
- Wer: 0.2681

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 5.0143        | 2.7778  | 200  | 3.0948          | 1.0    |
| 3.0375        | 5.5556  | 400  | 2.8972          | 1.0    |
| 2.7913        | 8.3333  | 600  | 2.3748          | 1.0    |
| 2.1375        | 11.1111 | 800  | 1.0610          | 0.9128 |
| 1.1118        | 13.8889 | 1000 | 0.3242          | 0.4894 |
| 0.5767        | 16.6667 | 1200 | 0.1737          | 0.4128 |
| 0.3823        | 19.4444 | 1400 | 0.0890          | 0.3681 |
| 0.2494        | 22.2222 | 1600 | 0.0470          | 0.3553 |
| 0.2165        | 25.0    | 1800 | 0.0585          | 0.3213 |
| 0.1548        | 27.7778 | 2000 | 0.0266          | 0.3106 |
| 0.1225        | 30.5556 | 2200 | 0.0248          | 0.3043 |
| 0.1104        | 33.3333 | 2400 | 0.0148          | 0.2830 |
| 0.1041        | 36.1111 | 2600 | 0.0130          | 0.2809 |
| 0.0872        | 38.8889 | 2800 | 0.0058          | 0.2745 |
| 0.0722        | 41.6667 | 3000 | 0.0045          | 0.2617 |
| 0.0721        | 44.4444 | 3200 | 0.0053          | 0.2723 |
| 0.0593        | 47.2222 | 3400 | 0.0059          | 0.2723 |
| 0.0625        | 50.0    | 3600 | 0.0042          | 0.2638 |
| 0.0555        | 52.7778 | 3800 | 0.0021          | 0.2638 |
| 0.0462        | 55.5556 | 4000 | 0.0043          | 0.2702 |
| 0.0381        | 58.3333 | 4200 | 0.0012          | 0.2638 |
| 0.0364        | 61.1111 | 4400 | 0.0022          | 0.2660 |
| 0.0351        | 63.8889 | 4600 | 0.0012          | 0.2681 |
| 0.0308        | 66.6667 | 4800 | 0.0024          | 0.2681 |
| 0.0255        | 69.4444 | 5000 | 0.0011          | 0.2638 |
| 0.0234        | 72.2222 | 5200 | 0.0006          | 0.2702 |
| 0.0269        | 75.0    | 5400 | 0.0003          | 0.2617 |
| 0.0186        | 77.7778 | 5600 | 0.0006          | 0.2638 |
| 0.0184        | 80.5556 | 5800 | 0.0007          | 0.2638 |
| 0.017         | 83.3333 | 6000 | 0.0002          | 0.2638 |
| 0.0124        | 86.1111 | 6200 | 0.0003          | 0.2702 |
| 0.0153        | 88.8889 | 6400 | 0.0002          | 0.2660 |
| 0.0151        | 91.6667 | 6600 | 0.0001          | 0.2681 |
| 0.0116        | 94.4444 | 6800 | 0.0001          | 0.2702 |
| 0.0089        | 97.2222 | 7000 | 0.0002          | 0.2702 |
| 0.0079        | 100.0   | 7200 | 0.0002          | 0.2681 |


### Framework versions

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