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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
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
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:
- Accuracy: 0.8830
- Loss: 0.4259
## 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: 5
- eval_batch_size: 5
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 0.7016 | 1.0 | 125 | 0.7933 | 0.6439 |
| 0.7121 | 2.0 | 250 | 0.5962 | 0.7870 |
| 0.4491 | 3.0 | 375 | 0.8782 | 0.4561 |
| 0.4606 | 4.0 | 500 | 0.8526 | 0.5664 |
| 0.425 | 5.0 | 625 | 0.8718 | 0.4652 |
| 0.4852 | 6.0 | 750 | 0.8397 | 0.5111 |
| 0.3023 | 7.0 | 875 | 0.8766 | 0.4319 |
| 0.2247 | 8.0 | 1000 | 0.8654 | 0.5093 |
| 0.4269 | 9.0 | 1125 | 0.8926 | 0.4148 |
| 0.348 | 10.0 | 1250 | 0.8846 | 0.3861 |
| 0.5049 | 11.0 | 1375 | 0.8814 | 0.4141 |
| 0.2305 | 12.0 | 1500 | 0.8878 | 0.3804 |
| 0.2839 | 13.0 | 1625 | 0.8990 | 0.3682 |
| 0.1739 | 14.0 | 1750 | 0.9022 | 0.3917 |
| 0.2808 | 15.0 | 1875 | 0.8926 | 0.4303 |
| 0.2306 | 16.0 | 2000 | 0.9006 | 0.3951 |
| 0.2766 | 17.0 | 2125 | 0.8974 | 0.4003 |
| 0.1212 | 18.0 | 2250 | 0.8910 | 0.3999 |
| 0.2822 | 19.0 | 2375 | 0.8766 | 0.4390 |
| 0.1391 | 20.0 | 2500 | 0.8830 | 0.4259 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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