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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: XLRS_FullDataset
results: []
datasets:
- timit-asr/timit_asr
language:
- en
base_model:
- facebook/wav2vec2-base
pipeline_tag: automatic-speech-recognition
metrics:
- wer
library_name: transformers
---
<!-- 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. -->
# XLRS_FullDataset
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3057
- Wer: 0.2697
## 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: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.5696 | 1.0 | 500 | 3.1546 | 1.0 |
| 2.491 | 2.01 | 1000 | 0.8309 | 0.7872 |
| 0.7519 | 3.01 | 1500 | 0.3648 | 0.4364 |
| 0.4704 | 4.02 | 2000 | 0.2998 | 0.3758 |
| 0.3385 | 5.02 | 2500 | 0.2639 | 0.3439 |
| 0.2837 | 6.02 | 3000 | 0.2604 | 0.3309 |
| 0.2233 | 7.03 | 3500 | 0.2734 | 0.3143 |
| 0.1997 | 8.03 | 4000 | 0.2676 | 0.3121 |
| 0.1717 | 9.04 | 4500 | 0.2489 | 0.2941 |
| 0.1558 | 10.04 | 5000 | 0.2777 | 0.2969 |
| 0.1497 | 11.04 | 5500 | 0.2693 | 0.2890 |
| 0.1326 | 12.05 | 6000 | 0.2844 | 0.2921 |
| 0.118 | 13.05 | 6500 | 0.2818 | 0.2969 |
| 0.119 | 14.06 | 7000 | 0.2798 | 0.2854 |
| 0.0991 | 15.06 | 7500 | 0.2765 | 0.2858 |
| 0.108 | 16.06 | 8000 | 0.2904 | 0.2794 |
| 0.0935 | 17.07 | 8500 | 0.2846 | 0.2773 |
| 0.0857 | 18.07 | 9000 | 0.3120 | 0.2812 |
| 0.0928 | 19.08 | 9500 | 0.3073 | 0.2820 |
| 0.0832 | 20.08 | 10000 | 0.2981 | 0.2808 |
| 0.0768 | 21.08 | 10500 | 0.3065 | 0.2807 |
| 0.0768 | 22.09 | 11000 | 0.2960 | 0.2766 |
| 0.0754 | 23.09 | 11500 | 0.3007 | 0.2783 |
| 0.063 | 24.1 | 12000 | 0.2918 | 0.2739 |
| 0.0614 | 25.1 | 12500 | 0.3144 | 0.2748 |
| 0.0628 | 26.1 | 13000 | 0.3074 | 0.2713 |
| 0.0595 | 27.11 | 13500 | 0.3103 | 0.2695 |
| 0.0616 | 28.11 | 14000 | 0.3108 | 0.2697 |
| 0.0587 | 29.12 | 14500 | 0.3057 | 0.2697 |
### Framework versions
- Transformers 4.17.0
- Pytorch 2.5.1+cu121
- Datasets 1.18.3
- Tokenizers 0.20.3 |