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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.8_da0.2
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. -->
# w2v2-base-pretrained_lr5e-5_at0.8_da0.2
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co./facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3279
- Wer: 0.2674
## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 25.9775 | 25.0 | 250 | 4.0805 | 1.0 |
| 3.4724 | 50.0 | 500 | 3.1777 | 1.0 |
| 3.0775 | 75.0 | 750 | 3.0307 | 1.0 |
| 2.7225 | 100.0 | 1000 | 2.2425 | 1.0 |
| 0.8725 | 125.0 | 1250 | 1.5857 | 0.4584 |
| 0.1745 | 150.0 | 1500 | 1.8015 | 0.3503 |
| 0.0937 | 175.0 | 1750 | 1.8837 | 0.3131 |
| 0.0645 | 200.0 | 2000 | 2.0461 | 0.2947 |
| 0.0528 | 225.0 | 2250 | 2.1465 | 0.2853 |
| 0.0366 | 250.0 | 2500 | 2.1419 | 0.2875 |
| 0.0336 | 275.0 | 2750 | 2.1437 | 0.2755 |
| 0.026 | 300.0 | 3000 | 2.1733 | 0.2717 |
| 0.0247 | 325.0 | 3250 | 2.2546 | 0.2683 |
| 0.0207 | 350.0 | 3500 | 2.2603 | 0.2700 |
| 0.0185 | 375.0 | 3750 | 2.3492 | 0.2670 |
| 0.0186 | 400.0 | 4000 | 2.3279 | 0.2674 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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