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

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: 0.4542
- Wer: 0.3208

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.2929        | 2.8633  | 200  | 2.3482          | 1.0    |
| 0.9068        | 5.7194  | 400  | 0.2885          | 0.5495 |
| 0.1691        | 8.5755  | 600  | 0.2612          | 0.3732 |
| 0.0828        | 11.4317 | 800  | 0.2968          | 0.3595 |
| 0.0473        | 14.2878 | 1000 | 0.3520          | 0.3515 |
| 0.0428        | 17.1439 | 1200 | 0.3341          | 0.3595 |
| 0.0358        | 20.0    | 1400 | 0.3301          | 0.3345 |
| 0.0267        | 22.8633 | 1600 | 0.3461          | 0.3242 |
| 0.0247        | 25.7194 | 1800 | 0.3533          | 0.3333 |
| 0.0219        | 28.5755 | 2000 | 0.3746          | 0.3242 |
| 0.0245        | 31.4317 | 2200 | 0.3684          | 0.3254 |
| 0.0151        | 34.2878 | 2400 | 0.3780          | 0.3197 |
| 0.0119        | 37.1439 | 2600 | 0.3322          | 0.3220 |
| 0.0151        | 40.0    | 2800 | 0.3688          | 0.3231 |
| 0.0131        | 42.8633 | 3000 | 0.3895          | 0.3231 |
| 0.0118        | 45.7194 | 3200 | 0.4120          | 0.3242 |
| 0.0079        | 48.5755 | 3400 | 0.4206          | 0.3231 |
| 0.0062        | 51.4317 | 3600 | 0.4137          | 0.3242 |
| 0.0059        | 54.2878 | 3800 | 0.3937          | 0.3220 |
| 0.0085        | 57.1439 | 4000 | 0.4004          | 0.3208 |
| 0.0068        | 60.0    | 4200 | 0.4266          | 0.3242 |
| 0.0065        | 62.8633 | 4400 | 0.3980          | 0.3208 |
| 0.0067        | 65.7194 | 4600 | 0.3957          | 0.3208 |
| 0.0051        | 68.5755 | 4800 | 0.4251          | 0.3220 |
| 0.0035        | 71.4317 | 5000 | 0.4428          | 0.3220 |
| 0.0047        | 74.2878 | 5200 | 0.4380          | 0.3231 |
| 0.0034        | 77.1439 | 5400 | 0.4388          | 0.3220 |
| 0.0033        | 80.0    | 5600 | 0.4544          | 0.3197 |
| 0.002         | 82.8633 | 5800 | 0.4368          | 0.3197 |
| 0.0042        | 85.7194 | 6000 | 0.4402          | 0.3197 |
| 0.0028        | 88.5755 | 6200 | 0.4482          | 0.3220 |
| 0.002         | 91.4317 | 6400 | 0.4547          | 0.3208 |
| 0.0012        | 94.2878 | 6600 | 0.4565          | 0.3208 |
| 0.0017        | 97.1439 | 6800 | 0.4542          | 0.3208 |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0