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---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-base-960h-no-softmax-quality-daps
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-base-960h-no-softmax-quality-daps
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0422
- Accuracy: 0.9925
## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6897 | 0.9630 | 13 | 0.6386 | 0.9318 |
| 0.6402 | 2.0 | 27 | 0.3482 | 0.9943 |
| 0.2867 | 2.9630 | 40 | 0.1576 | 0.9938 |
| 0.1729 | 4.0 | 54 | 0.0806 | 0.9960 |
| 0.1058 | 4.9630 | 67 | 0.0539 | 0.9952 |
| 0.0542 | 6.0 | 81 | 0.0446 | 0.9947 |
| 0.0393 | 6.9630 | 94 | 0.0409 | 0.9943 |
| 0.0398 | 8.0 | 108 | 0.0401 | 0.9938 |
| 0.0325 | 8.9630 | 121 | 0.0459 | 0.9921 |
| 0.0251 | 10.0 | 135 | 0.0444 | 0.9925 |
| 0.0331 | 10.9630 | 148 | 0.0418 | 0.9930 |
| 0.0185 | 12.0 | 162 | 0.0373 | 0.9930 |
| 0.0254 | 12.9630 | 175 | 0.0367 | 0.9930 |
| 0.0238 | 14.0 | 189 | 0.0423 | 0.9925 |
| 0.023 | 14.4444 | 195 | 0.0422 | 0.9925 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.12.0
- Tokenizers 0.19.1
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