---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-E10_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-E10_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: 4.3504
- Cer: 92.7732

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 57.6816       | 0.1289 | 200  | 6.9208          | 100.0   |
| 30.0241       | 0.2579 | 400  | 4.9760          | 99.2186 |
| 25.7956       | 0.3868 | 600  | 5.0354          | 93.9248 |
| 26.9553       | 0.5158 | 800  | 4.7842          | 94.0834 |
| 10.9188       | 0.6447 | 1000 | 5.0386          | 93.0141 |
| 4.8381        | 0.7737 | 1200 | 4.8832          | 93.1669 |
| 5.8977        | 0.9026 | 1400 | 4.7683          | 93.9953 |
| 5.9801        | 1.0316 | 1600 | 4.4577          | 94.1011 |
| 4.624         | 1.1605 | 1800 | 4.4622          | 93.7720 |
| 4.5279        | 1.2895 | 2000 | 4.4747          | 93.8132 |
| 4.5665        | 1.4184 | 2200 | 4.4467          | 93.8895 |
| 4.5274        | 1.5474 | 2400 | 4.4445          | 94.0541 |
| 4.5253        | 1.6763 | 2600 | 4.4448          | 93.8719 |
| 4.4933        | 1.8053 | 2800 | 4.4757          | 93.5723 |
| 4.4909        | 1.9342 | 3000 | 4.4318          | 93.5781 |
| 4.4942        | 2.0632 | 3200 | 4.4363          | 93.0905 |
| 4.3985        | 2.1921 | 3400 | 4.4396          | 92.9965 |
| 4.3714        | 2.3211 | 3600 | 4.3876          | 92.6263 |
| 4.3536        | 2.4500 | 3800 | 4.3960          | 92.9788 |
| 4.3598        | 2.5790 | 4000 | 4.3974          | 92.9553 |
| 4.3408        | 2.7079 | 4200 | 4.3550          | 92.7497 |
| 4.3141        | 2.8369 | 4400 | 4.3579          | 92.9377 |
| 4.2794        | 2.9658 | 4600 | 4.3504          | 92.7732 |


### Framework versions

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