---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-E50_speed2
  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_speed2

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: 1.0444
- Cer: 21.8625

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

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 37.5369       | 0.1289 | 200  | 5.2051          | 100.0   |
| 4.8991        | 0.2579 | 400  | 4.6157          | 100.0   |
| 4.7556        | 0.3868 | 600  | 4.6579          | 100.0   |
| 4.7401        | 0.5158 | 800  | 4.7246          | 100.0   |
| 4.6787        | 0.6447 | 1000 | 4.5941          | 100.0   |
| 4.6531        | 0.7737 | 1200 | 4.5238          | 100.0   |
| 4.5631        | 0.9026 | 1400 | 4.3757          | 100.0   |
| 3.8885        | 1.0316 | 1600 | 3.1641          | 57.0682 |
| 2.9165        | 1.1605 | 1800 | 2.6892          | 47.8202 |
| 2.4332        | 1.2895 | 2000 | 2.2163          | 40.8226 |
| 2.1146        | 1.4184 | 2200 | 1.9082          | 35.0705 |
| 1.9011        | 1.5474 | 2400 | 1.8199          | 35.3702 |
| 1.7622        | 1.6763 | 2600 | 1.6833          | 32.0564 |
| 1.6191        | 1.8053 | 2800 | 1.5709          | 30.7109 |
| 1.4782        | 1.9342 | 3000 | 1.4401          | 28.7427 |
| 1.3359        | 2.0632 | 3200 | 1.3604          | 27.1093 |
| 1.2158        | 2.1921 | 3400 | 1.2156          | 24.7650 |
| 1.1436        | 2.3211 | 3600 | 1.1927          | 24.3948 |
| 1.1092        | 2.4500 | 3800 | 1.1650          | 24.4712 |
| 1.0546        | 2.5790 | 4000 | 1.0929          | 22.8966 |
| 1.0207        | 2.7079 | 4200 | 1.0990          | 22.8790 |
| 0.9799        | 2.8369 | 4400 | 1.0580          | 22.2679 |
| 0.9561        | 2.9658 | 4600 | 1.0444          | 21.8625 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3