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---
license: apache-2.0
base_model: smutuvi/wav2vec2-large-xlsr-sw
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-sw_ndizi_782_100_epochs
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-large-xlsr-sw_ndizi_782_100_epochs
This model is a fine-tuned version of [smutuvi/wav2vec2-large-xlsr-sw](https://huggingface.co/smutuvi/wav2vec2-large-xlsr-sw) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1009
- Wer: 0.4847
## 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: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.4035 | 4.79 | 400 | 1.2492 | 0.5608 |
| 0.8489 | 9.58 | 800 | 1.0208 | 0.5114 |
| 0.632 | 14.37 | 1200 | 1.3292 | 0.5306 |
| 0.4653 | 19.16 | 1600 | 1.5159 | 0.5109 |
| 0.3598 | 23.95 | 2000 | 1.4650 | 0.5450 |
| 0.2776 | 28.74 | 2400 | 1.8568 | 0.5124 |
| 0.218 | 33.53 | 2800 | 2.0913 | 0.5188 |
| 0.1711 | 38.32 | 3200 | 2.2706 | 0.5035 |
| 0.141 | 43.11 | 3600 | 2.3050 | 0.5094 |
| 0.1162 | 47.9 | 4000 | 2.4539 | 0.5025 |
| 0.1007 | 52.69 | 4400 | 2.4754 | 0.5020 |
| 0.0881 | 57.49 | 4800 | 2.5512 | 0.5030 |
| 0.0816 | 62.28 | 5200 | 2.6458 | 0.5064 |
| 0.0792 | 67.07 | 5600 | 2.7869 | 0.5025 |
| 0.06 | 71.86 | 6000 | 2.9063 | 0.5040 |
| 0.0594 | 76.65 | 6400 | 2.8363 | 0.5049 |
| 0.0527 | 81.44 | 6800 | 3.0801 | 0.4921 |
| 0.0473 | 86.23 | 7200 | 3.0959 | 0.4867 |
| 0.0471 | 91.02 | 7600 | 3.0942 | 0.4852 |
| 0.0405 | 95.81 | 8000 | 3.1009 | 0.4847 |
### Framework versions
- Transformers 4.37.1
- Pytorch 2.2.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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