---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2_l2arctic
  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. -->

# wav2vec2_l2arctic

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5487
- Wer: 0.1460
- Cer: 0.0904

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 6.3356        | 0.9941  | 84   | 4.6295          | 1.0    | 1.0    |
| 3.5484        | 2.0     | 169  | 3.5272          | 1.0    | 1.0    |
| 3.5314        | 2.9941  | 253  | 3.5110          | 1.0    | 1.0    |
| 3.5084        | 4.0     | 338  | 3.5019          | 1.0    | 1.0    |
| 3.3271        | 4.9941  | 422  | 3.2417          | 1.0    | 1.0    |
| 1.6302        | 6.0     | 507  | 1.0777          | 0.3444 | 0.3220 |
| 0.7834        | 6.9941  | 591  | 0.6123          | 0.1780 | 0.1189 |
| 0.6067        | 8.0     | 676  | 0.5169          | 0.1550 | 0.0983 |
| 0.534         | 8.9941  | 760  | 0.5095          | 0.1549 | 0.0993 |
| 0.4711        | 10.0    | 845  | 0.4976          | 0.1524 | 0.0962 |
| 0.3979        | 10.9941 | 929  | 0.4951          | 0.1497 | 0.0937 |
| 0.354         | 12.0    | 1014 | 0.5012          | 0.1505 | 0.0943 |
| 0.3415        | 12.9941 | 1098 | 0.5090          | 0.1489 | 0.0937 |
| 0.295         | 14.0    | 1183 | 0.5098          | 0.1488 | 0.0944 |
| 0.2917        | 14.9941 | 1267 | 0.5296          | 0.1507 | 0.0946 |
| 0.2397        | 16.0    | 1352 | 0.5315          | 0.1507 | 0.0944 |
| 0.2713        | 16.9941 | 1436 | 0.5367          | 0.1467 | 0.0913 |
| 0.2153        | 18.0    | 1521 | 0.5456          | 0.1483 | 0.0924 |
| 0.206         | 18.9941 | 1605 | 0.5464          | 0.1471 | 0.0914 |
| 0.2488        | 19.8817 | 1680 | 0.5487          | 0.1460 | 0.0904 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1