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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-1b-bemba-genbed-combined
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. -->
# xls-r-1b-bemba-genbed-combined
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5103
- Wer: 0.7252
## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log | 0.1375 | 100 | 3.2454 | 1.0 |
| No log | 0.2749 | 200 | 2.9592 | 1.0 |
| No log | 0.4124 | 300 | 1.0579 | 1.0633 |
| No log | 0.5498 | 400 | 0.8291 | 0.9390 |
| 2.3726 | 0.6873 | 500 | 0.9104 | 0.9572 |
| 2.3726 | 0.8247 | 600 | 0.7652 | 0.8985 |
| 2.3726 | 0.9622 | 700 | 0.6910 | 0.8788 |
| 2.3726 | 1.0997 | 800 | 0.5304 | 0.7518 |
| 2.3726 | 1.2371 | 900 | 0.5304 | 0.7565 |
| 0.7002 | 1.3746 | 1000 | 0.5120 | 0.7657 |
| 0.7002 | 1.5120 | 1100 | 0.4937 | 0.7343 |
| 0.7002 | 1.6495 | 1200 | 0.4805 | 0.7139 |
| 0.7002 | 1.7869 | 1300 | 0.4803 | 0.7177 |
| 0.7002 | 1.9244 | 1400 | 0.4576 | 0.6875 |
| 0.5954 | 2.0619 | 1500 | 0.4863 | 0.7114 |
| 0.5954 | 2.1993 | 1600 | 0.5060 | 0.7316 |
| 0.5954 | 2.3368 | 1700 | 0.5103 | 0.7252 |
### Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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