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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_lr1e-4_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_lr1e-4_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: 1.3297
- Wer: 0.2683
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 200
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 23.6917 | 10.0 | 100 | 3.6026 | 1.0 |
| 3.259 | 20.0 | 200 | 3.1696 | 1.0 |
| 3.1152 | 30.0 | 300 | 3.1344 | 1.0 |
| 3.0799 | 40.0 | 400 | 3.0976 | 1.0 |
| 3.0793 | 50.0 | 500 | 3.0977 | 1.0 |
| 3.0692 | 60.0 | 600 | 3.0992 | 1.0 |
| 3.0604 | 70.0 | 700 | 3.1350 | 1.0 |
| 3.0397 | 80.0 | 800 | 3.0537 | 1.0 |
| 2.9847 | 90.0 | 900 | 2.9905 | 1.0 |
| 2.5926 | 100.0 | 1000 | 2.2350 | 1.0077 |
| 0.9017 | 110.0 | 1100 | 1.2152 | 0.6301 |
| 0.2326 | 120.0 | 1200 | 1.2279 | 0.4524 |
| 0.1364 | 130.0 | 1300 | 1.2103 | 0.4238 |
| 0.0935 | 140.0 | 1400 | 1.1953 | 0.3926 |
| 0.0759 | 150.0 | 1500 | 1.3237 | 0.3516 |
| 0.0599 | 160.0 | 1600 | 1.3929 | 0.3050 |
| 0.0438 | 170.0 | 1700 | 1.3132 | 0.2717 |
| 0.0389 | 180.0 | 1800 | 1.3469 | 0.2666 |
| 0.0355 | 190.0 | 1900 | 1.3029 | 0.2691 |
| 0.03 | 200.0 | 2000 | 1.3297 | 0.2683 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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