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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: finetune_add_transformer
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. -->
# finetune_add_transformer
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2934
- Cer: 0.0724
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 4.2464 | 5.95 | 500 | 0.7569 | 0.2284 |
| 0.5463 | 11.9 | 1000 | 0.3276 | 0.0814 |
| 0.3545 | 17.86 | 1500 | 0.3084 | 0.0779 |
| 0.2841 | 23.81 | 2000 | 0.3200 | 0.0756 |
| 0.232 | 29.76 | 2500 | 0.3181 | 0.0735 |
| 0.1922 | 35.71 | 3000 | 0.3480 | 0.0731 |
| 0.1601 | 41.67 | 3500 | 0.3990 | 0.0742 |
| 0.1362 | 47.62 | 4000 | 0.4304 | 0.0736 |
| 0.1165 | 53.57 | 4500 | 0.4847 | 0.0746 |
| 0.0994 | 59.52 | 5000 | 0.5250 | 0.0761 |
| 0.0876 | 65.48 | 5500 | 0.5628 | 0.0740 |
| 0.0791 | 71.43 | 6000 | 0.5871 | 0.0742 |
| 0.0716 | 77.38 | 6500 | 0.5933 | 0.0729 |
| 0.0661 | 83.33 | 7000 | 0.6238 | 0.0739 |
| 0.0605 | 89.29 | 7500 | 0.6623 | 0.0742 |
| 0.0569 | 95.24 | 8000 | 0.6638 | 0.0729 |
| 0.0535 | 101.19 | 8500 | 0.6681 | 0.0730 |
| 0.0498 | 107.14 | 9000 | 0.6815 | 0.0733 |
| 0.0491 | 113.1 | 9500 | 0.6818 | 0.0733 |
| 0.0471 | 119.05 | 10000 | 0.6810 | 0.0732 |
### Framework versions
- Transformers 4.17.0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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