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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2_milDB
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_milDB
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9031
- Wer: 1.0
## 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: 32
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:---:|
| 1.9166 | 10.9890 | 1000 | 1.6068 | 1.0 |
| 1.2813 | 21.9780 | 2000 | 1.6121 | 1.0 |
| 1.8313 | 32.9670 | 3000 | 1.8892 | 1.0 |
| 1.8958 | 43.9560 | 4000 | 1.8899 | 1.0 |
| 1.897 | 54.9451 | 5000 | 1.9031 | 1.0 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.4.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0
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