---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-E50_speed
  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-E50_speed

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7201
- Cer: 34.5747

## 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: 50
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 38.2863       | 0.1289 | 200  | 4.9788          | 100.0   |
| 4.8884        | 0.2579 | 400  | 4.7635          | 100.0   |
| 4.7532        | 0.3868 | 600  | 4.6460          | 100.0   |
| 4.7285        | 0.5158 | 800  | 4.6380          | 100.0   |
| 4.6656        | 0.6447 | 1000 | 4.6877          | 100.0   |
| 4.6484        | 0.7737 | 1200 | 4.6586          | 100.0   |
| 4.6328        | 0.9026 | 1400 | 4.6110          | 100.0   |
| 4.5589        | 1.0316 | 1600 | 4.5007          | 100.0   |
| 4.4938        | 1.1605 | 1800 | 4.4103          | 98.0557 |
| 4.3191        | 1.2895 | 2000 | 4.2620          | 95.5768 |
| 3.9702        | 1.4184 | 2200 | 3.6438          | 68.0099 |
| 3.3814        | 1.5474 | 2400 | 3.1348          | 60.4323 |
| 2.9655        | 1.6763 | 2600 | 2.9093          | 59.5865 |
| 2.7274        | 1.8053 | 2800 | 2.5505          | 51.1396 |
| 2.5117        | 1.9342 | 3000 | 2.2604          | 46.0644 |
| 2.3308        | 2.0632 | 3200 | 2.0918          | 42.4871 |
| 2.1864        | 2.1921 | 3400 | 2.0284          | 41.0832 |
| 2.0692        | 2.3211 | 3600 | 1.9906          | 40.9774 |
| 2.0208        | 2.4500 | 3800 | 1.9112          | 38.6278 |
| 1.9439        | 2.5790 | 4000 | 1.8649          | 38.3870 |
| 1.8928        | 2.7079 | 4200 | 1.7703          | 35.7789 |
| 1.8225        | 2.8369 | 4400 | 1.7312          | 34.8508 |
| 1.8341        | 2.9658 | 4600 | 1.7201          | 34.5747 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1