---
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-se-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-se-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: 0.0008
- Wer: 0.2106

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.9119        | 4.2553  | 200  | 3.0710          | 1.0    |
| 3.0199        | 8.5106  | 400  | 2.8618          | 1.0    |
| 2.7311        | 12.7660 | 600  | 2.2436          | 0.9957 |
| 1.7526        | 17.0213 | 800  | 0.5282          | 0.6234 |
| 0.7948        | 21.2766 | 1000 | 0.1705          | 0.3894 |
| 0.4432        | 25.5319 | 1200 | 0.1006          | 0.3149 |
| 0.2996        | 29.7872 | 1400 | 0.0629          | 0.2660 |
| 0.2087        | 34.0426 | 1600 | 0.0243          | 0.2532 |
| 0.1572        | 38.2979 | 1800 | 0.0223          | 0.2362 |
| 0.1222        | 42.5532 | 2000 | 0.0177          | 0.2404 |
| 0.1003        | 46.8085 | 2200 | 0.0069          | 0.2298 |
| 0.0897        | 51.0638 | 2400 | 0.0074          | 0.2234 |
| 0.0686        | 55.3191 | 2600 | 0.0058          | 0.2149 |
| 0.0649        | 59.5745 | 2800 | 0.0028          | 0.2064 |
| 0.0481        | 63.8298 | 3000 | 0.0027          | 0.2064 |
| 0.0504        | 68.0851 | 3200 | 0.0028          | 0.2085 |
| 0.0416        | 72.3404 | 3400 | 0.0042          | 0.1936 |
| 0.0317        | 76.5957 | 3600 | 0.0023          | 0.2021 |
| 0.0326        | 80.8511 | 3800 | 0.0010          | 0.2043 |
| 0.026         | 85.1064 | 4000 | 0.0009          | 0.2085 |
| 0.0233        | 89.3617 | 4200 | 0.0009          | 0.2085 |
| 0.0202        | 93.6170 | 4400 | 0.0008          | 0.2106 |
| 0.0235        | 97.8723 | 4600 | 0.0008          | 0.2106 |


### Framework versions

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