---
license: apache-2.0
base_model: facebook/wav2vec2-conformer-rel-pos-large
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-conformer-rel-pos-jv-openslr
  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-conformer-rel-pos-jv-openslr

This model is a fine-tuned version of [facebook/wav2vec2-conformer-rel-pos-large](https://huggingface.co/facebook/wav2vec2-conformer-rel-pos-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2470
- Wer: 0.1227

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 75
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 0.5826        | 2.8329  | 2000  | 0.4733          | 0.4445 |
| 0.3478        | 5.6657  | 4000  | 0.3538          | 0.3191 |
| 0.2532        | 8.4986  | 6000  | 0.3085          | 0.2646 |
| 0.2028        | 11.3314 | 8000  | 0.2799          | 0.2467 |
| 0.1628        | 14.1643 | 10000 | 0.2623          | 0.2095 |
| 0.1407        | 16.9972 | 12000 | 0.2510          | 0.2068 |
| 0.1154        | 19.8300 | 14000 | 0.2922          | 0.1937 |
| 0.1044        | 22.6629 | 16000 | 0.2660          | 0.1730 |
| 0.0929        | 25.4958 | 18000 | 0.2818          | 0.1868 |
| 0.0798        | 28.3286 | 20000 | 0.2573          | 0.1633 |
| 0.074         | 31.1615 | 22000 | 0.2398          | 0.1647 |
| 0.0678        | 33.9943 | 24000 | 0.2601          | 0.1606 |
| 0.0628        | 36.8272 | 26000 | 0.2627          | 0.1613 |
| 0.057         | 39.6601 | 28000 | 0.2393          | 0.1468 |
| 0.0547        | 42.4929 | 30000 | 0.2662          | 0.1585 |
| 0.0512        | 45.3258 | 32000 | 0.2544          | 0.1502 |
| 0.0446        | 48.1586 | 34000 | 0.2542          | 0.1502 |
| 0.045         | 50.9915 | 36000 | 0.2624          | 0.1516 |
| 0.0403        | 53.8244 | 38000 | 0.2487          | 0.1420 |
| 0.0378        | 56.6572 | 40000 | 0.2498          | 0.1330 |
| 0.0353        | 59.4901 | 42000 | 0.2495          | 0.1309 |
| 0.0337        | 62.3229 | 44000 | 0.2505          | 0.1316 |
| 0.029         | 65.1558 | 46000 | 0.2373          | 0.1247 |
| 0.0277        | 67.9887 | 48000 | 0.2543          | 0.1282 |
| 0.0283        | 70.8215 | 50000 | 0.2547          | 0.1234 |
| 0.0275        | 73.6544 | 52000 | 0.2470          | 0.1227 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.2.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1