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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_da0.5
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_da0.5
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: 2.3736
- Wer: 0.1858
## 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 |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 20.81 | 10.87 | 250 | 3.8675 | 1.0 |
| 3.2992 | 21.74 | 500 | 3.1858 | 1.0 |
| 3.0813 | 32.61 | 750 | 3.0758 | 1.0 |
| 2.3718 | 43.48 | 1000 | 1.3480 | 0.8266 |
| 0.3075 | 54.35 | 1250 | 1.6498 | 0.2290 |
| 0.1081 | 65.22 | 1500 | 1.8213 | 0.2012 |
| 0.0732 | 76.09 | 1750 | 1.8933 | 0.1952 |
| 0.0517 | 86.96 | 2000 | 2.0154 | 0.2059 |
| 0.0386 | 97.83 | 2250 | 2.0444 | 0.1948 |
| 0.0323 | 108.7 | 2500 | 2.2603 | 0.2003 |
| 0.0272 | 119.57 | 2750 | 2.2578 | 0.1952 |
| 0.0234 | 130.43 | 3000 | 2.2854 | 0.1880 |
| 0.0203 | 141.3 | 3250 | 2.3553 | 0.1867 |
| 0.0181 | 152.17 | 3500 | 2.3723 | 0.1905 |
| 0.0165 | 163.04 | 3750 | 2.3793 | 0.1854 |
| 0.016 | 173.91 | 4000 | 2.3736 | 0.1858 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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